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Sequence AlignmentSequence Analysis, ProteinSoftwareAlgorithmsMolecular Sequence DataAmino Acid SequenceComputational BiologyPhylogenySequence Homology, Amino AcidProteinsDatabases, ProteinSequence Analysis, DNAModels, MolecularConserved SequenceInternetBase SequenceEvolution, MolecularUser-Computer InterfaceSoftware ValidationStructural Homology, ProteinSequence AnalysisSequence Analysis, RNAProtein Structure, TertiaryComputing MethodologiesSequence HomologyComputer GraphicsProtein Structure, SecondaryMarkov ChainsProtein ConformationGenomicsComputer SimulationDatabases, GeneticSequence Homology, Nucleic AcidGenomeBinding SitesDatabases, FactualWord ProcessingDatabases, Nucleic AcidModels, GeneticModels, StatisticalInformation Storage and RetrievalPattern Recognition, AutomatedCloning, MolecularAmino Acid MotifsConsensus SequenceLikelihood FunctionsReproducibility of ResultsSoftware DesignMutagenesis, Site-DirectedINDEL MutationProgramming LanguagesCluster AnalysisRNAEscherichia coliProtein FoldingDatabase Management SystemsBacterial ProteinsNucleic Acid ConformationBone MalalignmentMultigene FamilyModels, ChemicalMutationArtificial IntelligenceAmino Acid SubstitutionSpecies SpecificityCatalytic DomainDNAProtein BindingStructure-Activity RelationshipSubstrate SpecificityCrystallography, X-RaySensitivity and SpecificityGenetic VariationExpressed Sequence TagsWork SimplificationBayes TheoremCatalysisRecombinant ProteinsProbabilityDNA, ComplementaryRNA, UntranslatedOpen Reading FramesEntropyArchaeaSarcocystidaeDNA PrimersBase PairingComputersGenome, HumanBenchmarkingData CompressionQuality ControlChromosome MappingMonte Carlo MethodGenome, BacterialGenome, ViralData Interpretation, StatisticalComputer Communication NetworksPan troglodytesTetraodontiformesKineticsPolymerase Chain ReactionRNA, RibosomalGenes, OverlappingEnzyme StabilityNucleotide MotifsAmino AcidsPlant ProteinsExonsBiological EvolutionGene Expression ProfilingProtein EngineeringHypermediaMolecular Sequence AnnotationCodonProtein Structure, QuaternaryDNA, IntergenicHigh-Throughput Nucleotide SequencingDNA, BacterialGenes, BacterialBacteriaGene LibraryKnee JointMathematical ComputingAutomationGenome, PlantSystems IntegrationCircular DichroismNeural Networks (Computer)Membrane ProteinsHydrogen BondingIntronsEvaluation Studies as TopicEscherichia coli ProteinsHMG-Box DomainsCattleEukaryotic CellsRecombination, GeneticDNA Mutational AnalysisOryza sativaRNA, BacterialMammalsNucleotidesDNA Barcoding, TaxonomicSaccharomyces cerevisiaeViral ProteinsSolanaceaePeptidesSyntenySequence DeletionModels, TheoreticalDocumentationMutagenesisNational Library of Medicine (U.S.)Mutagenesis, InsertionalHistidineDNA, RibosomalLigandsArchaeal ProteinsCarrier ProteinsImaging, Three-DimensionalMolecular ConformationProkaryotic CellsPseudogenesDNA, ChloroplastDimerizationSurgery, Computer-AssistedEnzymesModels, BiologicalClassificationTranscription FactorsRNA, Ribosomal, 16SRepetitive Sequences, Nucleic AcidStatic ElectricityModels, StructuralProtein Interaction MappingThermodynamicsPeptide FragmentsPlantsTibiaCysteineMethanococcusBase CompositionMolecular StructureRNA, MessengerTime Factors
Sequence Alignment: The arrangement of two or more amino acid or base sequences from an organism or organisms in such a way as to align areas of the sequences sharing common properties. The degree of relatedness or homology between the sequences is predicted computationally or statistically based on weights assigned to the elements aligned between the sequences. This in turn can serve as a potential indicator of the genetic relatedness between the organisms.Sequence Analysis, Protein: A process that includes the determination of AMINO ACID SEQUENCE of a protein (or peptide, oligopeptide or peptide fragment) and the information analysis of the sequence.Software: Sequential operating programs and data which instruct the functioning of a digital computer.Algorithms: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.Molecular Sequence Data: Descriptions of specific amino acid, carbohydrate, or nucleotide sequences which have appeared in the published literature and/or are deposited in and maintained by databanks such as GENBANK, European Molecular Biology Laboratory (EMBL), National Biomedical Research Foundation (NBRF), or other sequence repositories.Amino Acid Sequence: The order of amino acids as they occur in a polypeptide chain. This is referred to as the primary structure of proteins. It is of fundamental importance in determining PROTEIN CONFORMATION.Computational Biology: A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets.Phylogeny: The relationships of groups of organisms as reflected by their genetic makeup.Sequence Homology, Amino Acid: The degree of similarity between sequences of amino acids. This information is useful for the analyzing genetic relatedness of proteins and species.Proteins: Linear POLYPEPTIDES that are synthesized on RIBOSOMES and may be further modified, crosslinked, cleaved, or assembled into complex proteins with several subunits. The specific sequence of AMINO ACIDS determines the shape the polypeptide will take, during PROTEIN FOLDING, and the function of the protein.Databases, Protein: Databases containing information about PROTEINS such as AMINO ACID SEQUENCE; PROTEIN CONFORMATION; and other properties.Sequence Analysis, DNA: A multistage process that includes cloning, physical mapping, subcloning, determination of the DNA SEQUENCE, and information analysis.Models, Molecular: Models used experimentally or theoretically to study molecular shape, electronic properties, or interactions; includes analogous molecules, computer-generated graphics, and mechanical structures.Conserved Sequence: A sequence of amino acids in a polypeptide or of nucleotides in DNA or RNA that is similar across multiple species. A known set of conserved sequences is represented by a CONSENSUS SEQUENCE. AMINO ACID MOTIFS are often composed of conserved sequences.Internet: A loose confederation of computer communication networks around the world. The networks that make up the Internet are connected through several backbone networks. The Internet grew out of the US Government ARPAnet project and was designed to facilitate information exchange.Base Sequence: The sequence of PURINES and PYRIMIDINES in nucleic acids and polynucleotides. It is also called nucleotide sequence.Evolution, Molecular: The process of cumulative change at the level of DNA; RNA; and PROTEINS, over successive generations.User-Computer Interface: The portion of an interactive computer program that issues messages to and receives commands from a user.Software Validation: The act of testing the software for compliance with a standard.Structural Homology, Protein: The degree of 3-dimensional shape similarity between proteins. It can be an indication of distant AMINO ACID SEQUENCE HOMOLOGY and used for rational DRUG DESIGN.Sequence Analysis: A multistage process that includes the determination of a sequence (protein, carbohydrate, etc.), its fragmentation and analysis, and the interpretation of the resulting sequence information.Sequence Analysis, RNA: A multistage process that includes cloning, physical mapping, subcloning, sequencing, and information analysis of an RNA SEQUENCE.Protein Structure, Tertiary: The level of protein structure in which combinations of secondary protein structures (alpha helices, beta sheets, loop regions, and motifs) pack together to form folded shapes called domains. Disulfide bridges between cysteines in two different parts of the polypeptide chain along with other interactions between the chains play a role in the formation and stabilization of tertiary structure. Small proteins usually consist of only one domain but larger proteins may contain a number of domains connected by segments of polypeptide chain which lack regular secondary structure.Computing Methodologies: Computer-assisted analysis and processing of problems in a particular area.Sequence Homology: The degree of similarity between sequences. Studies of AMINO ACID SEQUENCE HOMOLOGY and NUCLEIC ACID SEQUENCE HOMOLOGY provide useful information about the genetic relatedness of genes, gene products, and species.Computer Graphics: The process of pictorial communication, between human and computers, in which the computer input and output have the form of charts, drawings, or other appropriate pictorial representation.Protein Structure, Secondary: The level of protein structure in which regular hydrogen-bond interactions within contiguous stretches of polypeptide chain give rise to alpha helices, beta strands (which align to form beta sheets) or other types of coils. This is the first folding level of protein conformation.Markov Chains: A stochastic process such that the conditional probability distribution for a state at any future instant, given the present state, is unaffected by any additional knowledge of the past history of the system.Protein Conformation: The characteristic 3-dimensional shape of a protein, including the secondary, supersecondary (motifs), tertiary (domains) and quaternary structure of the peptide chain. PROTEIN STRUCTURE, QUATERNARY describes the conformation assumed by multimeric proteins (aggregates of more than one polypeptide chain).Genomics: The systematic study of the complete DNA sequences (GENOME) of organisms.Computer Simulation: Computer-based representation of physical systems and phenomena such as chemical processes.Databases, Genetic: Databases devoted to knowledge about specific genes and gene products.Sequence Homology, Nucleic Acid: The sequential correspondence of nucleotides in one nucleic acid molecule with those of another nucleic acid molecule. Sequence homology is an indication of the genetic relatedness of different organisms and gene function.Genome: The genetic complement of an organism, including all of its GENES, as represented in its DNA, or in some cases, its RNA.Binding Sites: The parts of a macromolecule that directly participate in its specific combination with another molecule.Databases, Factual: Extensive collections, reputedly complete, of facts and data garnered from material of a specialized subject area and made available for analysis and application. The collection can be automated by various contemporary methods for retrieval. The concept should be differentiated from DATABASES, BIBLIOGRAPHIC which is restricted to collections of bibliographic references.Word Processing: Text editing and storage functions using computer software.Databases, Nucleic Acid: Databases containing information about NUCLEIC ACIDS such as BASE SEQUENCE; SNPS; NUCLEIC ACID CONFORMATION; and other properties. Information about the DNA fragments kept in a GENE LIBRARY or GENOMIC LIBRARY is often maintained in DNA databases.Models, Genetic: Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.Models, Statistical: Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.Information Storage and Retrieval: Organized activities related to the storage, location, search, and retrieval of information.Pattern Recognition, Automated: In INFORMATION RETRIEVAL, machine-sensing or identification of visible patterns (shapes, forms, and configurations). (Harrod's Librarians' Glossary, 7th ed)Cloning, Molecular: The insertion of recombinant DNA molecules from prokaryotic and/or eukaryotic sources into a replicating vehicle, such as a plasmid or virus vector, and the introduction of the resultant hybrid molecules into recipient cells without altering the viability of those cells.Amino Acid Motifs: Commonly observed structural components of proteins formed by simple combinations of adjacent secondary structures. A commonly observed structure may be composed of a CONSERVED SEQUENCE which can be represented by a CONSENSUS SEQUENCE.Consensus Sequence: A theoretical representative nucleotide or amino acid sequence in which each nucleotide or amino acid is the one which occurs most frequently at that site in the different sequences which occur in nature. The phrase also refers to an actual sequence which approximates the theoretical consensus. A known CONSERVED SEQUENCE set is represented by a consensus sequence. Commonly observed supersecondary protein structures (AMINO ACID MOTIFS) are often formed by conserved sequences.Likelihood Functions: Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters.Reproducibility of Results: The statistical reproducibility of measurements (often in a clinical context), including the testing of instrumentation or techniques to obtain reproducible results. The concept includes reproducibility of physiological measurements, which may be used to develop rules to assess probability or prognosis, or response to a stimulus; reproducibility of occurrence of a condition; and reproducibility of experimental results.Software Design: Specifications and instructions applied to the software.Mutagenesis, Site-Directed: Genetically engineered MUTAGENESIS at a specific site in the DNA molecule that introduces a base substitution, or an insertion or deletion.INDEL Mutation: A mutation named with the blend of insertion and deletion. It refers to a length difference between two ALLELES where it is unknowable if the difference was originally caused by a SEQUENCE INSERTION or by a SEQUENCE DELETION. If the number of nucleotides in the insertion/deletion is not divisible by three, and it occurs in a protein coding region, it is also a FRAMESHIFT MUTATION.Programming Languages: Specific languages used to prepare computer programs.Cluster Analysis: A set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both.RNA: A polynucleotide consisting essentially of chains with a repeating backbone of phosphate and ribose units to which nitrogenous bases are attached. RNA is unique among biological macromolecules in that it can encode genetic information, serve as an abundant structural component of cells, and also possesses catalytic activity. (Rieger et al., Glossary of Genetics: Classical and Molecular, 5th ed)Escherichia coli: A species of gram-negative, facultatively anaerobic, rod-shaped bacteria (GRAM-NEGATIVE FACULTATIVELY ANAEROBIC RODS) commonly found in the lower part of the intestine of warm-blooded animals. It is usually nonpathogenic, but some strains are known to produce DIARRHEA and pyogenic infections. Pathogenic strains (virotypes) are classified by their specific pathogenic mechanisms such as toxins (ENTEROTOXIGENIC ESCHERICHIA COLI), etc.Protein Folding: Processes involved in the formation of TERTIARY PROTEIN STRUCTURE.Database Management Systems: Software designed to store, manipulate, manage, and control data for specific uses.Bacterial Proteins: Proteins found in any species of bacterium.Nucleic Acid Conformation: The spatial arrangement of the atoms of a nucleic acid or polynucleotide that results in its characteristic 3-dimensional shape.Bone Malalignment: Displacement of bones out of line in relation to joints. It may be congenital or traumatic in origin.Multigene Family: A set of genes descended by duplication and variation from some ancestral gene. Such genes may be clustered together on the same chromosome or dispersed on different chromosomes. Examples of multigene families include those that encode the hemoglobins, immunoglobulins, histocompatibility antigens, actins, tubulins, keratins, collagens, heat shock proteins, salivary glue proteins, chorion proteins, cuticle proteins, yolk proteins, and phaseolins, as well as histones, ribosomal RNA, and transfer RNA genes. The latter three are examples of reiterated genes, where hundreds of identical genes are present in a tandem array. (King & Stanfield, A Dictionary of Genetics, 4th ed)Models, Chemical: Theoretical representations that simulate the behavior or activity of chemical processes or phenomena; includes the use of mathematical equations, computers, and other electronic equipment.Mutation: Any detectable and heritable change in the genetic material that causes a change in the GENOTYPE and which is transmitted to daughter cells and to succeeding generations.Artificial Intelligence: Theory and development of COMPUTER SYSTEMS which perform tasks that normally require human intelligence. Such tasks may include speech recognition, LEARNING; VISUAL PERCEPTION; MATHEMATICAL COMPUTING; reasoning, PROBLEM SOLVING, DECISION-MAKING, and translation of language.Amino Acid Substitution: The naturally occurring or experimentally induced replacement of one or more AMINO ACIDS in a protein with another. If a functionally equivalent amino acid is substituted, the protein may retain wild-type activity. Substitution may also diminish, enhance, or eliminate protein function. Experimentally induced substitution is often used to study enzyme activities and binding site properties.Species Specificity: The restriction of a characteristic behavior, anatomical structure or physical system, such as immune response; metabolic response, or gene or gene variant to the members of one species. It refers to that property which differentiates one species from another but it is also used for phylogenetic levels higher or lower than the species.Catalytic Domain: The region of an enzyme that interacts with its substrate to cause the enzymatic reaction.DNA: A deoxyribonucleotide polymer that is the primary genetic material of all cells. Eukaryotic and prokaryotic organisms normally contain DNA in a double-stranded state, yet several important biological processes transiently involve single-stranded regions. DNA, which consists of a polysugar-phosphate backbone possessing projections of purines (adenine and guanine) and pyrimidines (thymine and cytosine), forms a double helix that is held together by hydrogen bonds between these purines and pyrimidines (adenine to thymine and guanine to cytosine).Protein Binding: The process in which substances, either endogenous or exogenous, bind to proteins, peptides, enzymes, protein precursors, or allied compounds. Specific protein-binding measures are often used as assays in diagnostic assessments.Structure-Activity Relationship: The relationship between the chemical structure of a compound and its biological or pharmacological activity. Compounds are often classed together because they have structural characteristics in common including shape, size, stereochemical arrangement, and distribution of functional groups.Substrate Specificity: A characteristic feature of enzyme activity in relation to the kind of substrate on which the enzyme or catalytic molecule reacts.Crystallography, X-Ray: The study of crystal structure using X-RAY DIFFRACTION techniques. (McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed)Sensitivity and Specificity: Binary classification measures to assess test results. Sensitivity or recall rate is the proportion of true positives. Specificity is the probability of correctly determining the absence of a condition. (From Last, Dictionary of Epidemiology, 2d ed)Genetic Variation: Genotypic differences observed among individuals in a population.Expressed Sequence Tags: Partial cDNA (DNA, COMPLEMENTARY) sequences that are unique to the cDNAs from which they were derived.Work Simplification: The construction or arrangement of a task so that it may be done with the greatest possible efficiency.Bayes Theorem: A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.Catalysis: The facilitation of a chemical reaction by material (catalyst) that is not consumed by the reaction.Recombinant Proteins: Proteins prepared by recombinant DNA technology.Probability: The study of chance processes or the relative frequency characterizing a chance process.DNA, Complementary: Single-stranded complementary DNA synthesized from an RNA template by the action of RNA-dependent DNA polymerase. cDNA (i.e., complementary DNA, not circular DNA, not C-DNA) is used in a variety of molecular cloning experiments as well as serving as a specific hybridization probe.RNA, Untranslated: RNA which does not code for protein but has some enzymatic, structural or regulatory function. Although ribosomal RNA (RNA, RIBOSOMAL) and transfer RNA (RNA, TRANSFER) are also untranslated RNAs they are not included in this scope.Open Reading Frames: A sequence of successive nucleotide triplets that are read as CODONS specifying AMINO ACIDS and begin with an INITIATOR CODON and end with a stop codon (CODON, TERMINATOR).Entropy: The measure of that part of the heat or energy of a system which is not available to perform work. Entropy increases in all natural (spontaneous and irreversible) processes. (From Dorland, 28th ed)Archaea: One of the three domains of life (the others being BACTERIA and Eukarya), formerly called Archaebacteria under the taxon Bacteria, but now considered separate and distinct. They are characterized by: (1) the presence of characteristic tRNAs and ribosomal RNAs; (2) the absence of peptidoglycan cell walls; (3) the presence of ether-linked lipids built from branched-chain subunits; and (4) their occurrence in unusual habitats. While archaea resemble bacteria in morphology and genomic organization, they resemble eukarya in their method of genomic replication. The domain contains at least four kingdoms: CRENARCHAEOTA; EURYARCHAEOTA; NANOARCHAEOTA; and KORARCHAEOTA.Sarcocystidae: A family of parasitic organisms in the order EIMERIIDAE. They form tissue-cysts in their intermediate hosts, ultimately leading to pathogenesis in the final hosts that includes various mammals (including humans) and birds. The most important genera include NEOSPORA; SARCOCYSTIS; and TOXOPLASMA.DNA Primers: Short sequences (generally about 10 base pairs) of DNA that are complementary to sequences of messenger RNA and allow reverse transcriptases to start copying the adjacent sequences of mRNA. Primers are used extensively in genetic and molecular biology techniques.Base Pairing: Pairing of purine and pyrimidine bases by HYDROGEN BONDING in double-stranded DNA or RNA.ComputersGenome, Human: The complete genetic complement contained in the DNA of a set of CHROMOSOMES in a HUMAN. The length of the human genome is about 3 billion base pairs.Benchmarking: Method of measuring performance against established standards of best practice.Data Compression: Information application based on a variety of coding methods to minimize the amount of data to be stored, retrieved, or transmitted. Data compression can be applied to various forms of data, such as images and signals. It is used to reduce costs and increase efficiency in the maintenance of large volumes of data.Quality Control: A system for verifying and maintaining a desired level of quality in a product or process by careful planning, use of proper equipment, continued inspection, and corrective action as required. (Random House Unabridged Dictionary, 2d ed)Chromosome Mapping: Any method used for determining the location of and relative distances between genes on a chromosome.Monte Carlo Method: In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993)Genome, Bacterial: The genetic complement of a BACTERIA as represented in its DNA.Genome, Viral: The complete genetic complement contained in a DNA or RNA molecule in a virus.Data Interpretation, Statistical: Application of statistical procedures to analyze specific observed or assumed facts from a particular study.Computer Communication Networks: A system containing any combination of computers, computer terminals, printers, audio or visual display devices, or telephones interconnected by telecommunications equipment or cables: used to transmit or receive information. (Random House Unabridged Dictionary, 2d ed)Pan troglodytes: The common chimpanzee, a species of the genus Pan, family HOMINIDAE. It lives in Africa, primarily in the tropical rainforests. There are a number of recognized subspecies.Tetraodontiformes: A small order of primarily marine fish containing 340 species. Most have a rotund or box-like shape. TETRODOTOXIN is found in their liver and ovaries.Kinetics: The rate dynamics in chemical or physical systems.Polymerase Chain Reaction: In vitro method for producing large amounts of specific DNA or RNA fragments of defined length and sequence from small amounts of short oligonucleotide flanking sequences (primers). The essential steps include thermal denaturation of the double-stranded target molecules, annealing of the primers to their complementary sequences, and extension of the annealed primers by enzymatic synthesis with DNA polymerase. The reaction is efficient, specific, and extremely sensitive. Uses for the reaction include disease diagnosis, detection of difficult-to-isolate pathogens, mutation analysis, genetic testing, DNA sequencing, and analyzing evolutionary relationships.RNA, Ribosomal: The most abundant form of RNA. Together with proteins, it forms the ribosomes, playing a structural role and also a role in ribosomal binding of mRNA and tRNAs. Individual chains are conventionally designated by their sedimentation coefficients. In eukaryotes, four large chains exist, synthesized in the nucleolus and constituting about 50% of the ribosome. (Dorland, 28th ed)Genes, Overlapping: Genes whose nucleotide sequences overlap to some degree. The overlapped sequences may involve structural or regulatory genes of eukaryotic or prokaryotic cells.Enzyme Stability: The extent to which an enzyme retains its structural conformation or its activity when subjected to storage, isolation, and purification or various other physical or chemical manipulations, including proteolytic enzymes and heat.Nucleotide Motifs: Commonly observed BASE SEQUENCE or nucleotide structural components which can be represented by a CONSENSUS SEQUENCE or a SEQUENCE LOGO.Amino Acids: Organic compounds that generally contain an amino (-NH2) and a carboxyl (-COOH) group. Twenty alpha-amino acids are the subunits which are polymerized to form proteins.Plant Proteins: Proteins found in plants (flowers, herbs, shrubs, trees, etc.). The concept does not include proteins found in vegetables for which VEGETABLE PROTEINS is available.Exons: The parts of a transcript of a split GENE remaining after the INTRONS are removed. They are spliced together to become a MESSENGER RNA or other functional RNA.Biological Evolution: The process of cumulative change over successive generations through which organisms acquire their distinguishing morphological and physiological characteristics.Gene Expression Profiling: The determination of the pattern of genes expressed at the level of GENETIC TRANSCRIPTION, under specific circumstances or in a specific cell.Protein Engineering: Procedures by which protein structure and function are changed or created in vitro by altering existing or synthesizing new structural genes that direct the synthesis of proteins with sought-after properties. Such procedures may include the design of MOLECULAR MODELS of proteins using COMPUTER GRAPHICS or other molecular modeling techniques; site-specific mutagenesis (MUTAGENESIS, SITE-SPECIFIC) of existing genes; and DIRECTED MOLECULAR EVOLUTION techniques to create new genes.Hypermedia: Computerized compilations of information units (text, sound, graphics, and/or video) interconnected by logical nonlinear linkages that enable users to follow optimal paths through the material and also the systems used to create and display this information. (From Thesaurus of ERIC Descriptors, 1994)Molecular Sequence Annotation: The addition of descriptive information about the function or structure of a molecular sequence to its MOLECULAR SEQUENCE DATA record.Codon: A set of three nucleotides in a protein coding sequence that specifies individual amino acids or a termination signal (CODON, TERMINATOR). Most codons are universal, but some organisms do not produce the transfer RNAs (RNA, TRANSFER) complementary to all codons. These codons are referred to as unassigned codons (CODONS, NONSENSE).Protein Structure, Quaternary: The characteristic 3-dimensional shape and arrangement of multimeric proteins (aggregates of more than one polypeptide chain).DNA, Intergenic: Any of the DNA in between gene-coding DNA, including untranslated regions, 5' and 3' flanking regions, INTRONS, non-functional pseudogenes, and non-functional repetitive sequences. This DNA may or may not encode regulatory functions.High-Throughput Nucleotide Sequencing: Techniques of nucleotide sequence analysis that increase the range, complexity, sensitivity, and accuracy of results by greatly increasing the scale of operations and thus the number of nucleotides, and the number of copies of each nucleotide sequenced. The sequencing may be done by analysis of the synthesis or ligation products, hybridization to preexisting sequences, etc.DNA, Bacterial: Deoxyribonucleic acid that makes up the genetic material of bacteria.Genes, Bacterial: The functional hereditary units of BACTERIA.Bacteria: One of the three domains of life (the others being Eukarya and ARCHAEA), also called Eubacteria. They are unicellular prokaryotic microorganisms which generally possess rigid cell walls, multiply by cell division, and exhibit three principal forms: round or coccal, rodlike or bacillary, and spiral or spirochetal. Bacteria can be classified by their response to OXYGEN: aerobic, anaerobic, or facultatively anaerobic; by the mode by which they obtain their energy: chemotrophy (via chemical reaction) or PHOTOTROPHY (via light reaction); for chemotrophs by their source of chemical energy: CHEMOLITHOTROPHY (from inorganic compounds) or chemoorganotrophy (from organic compounds); and by their source for CARBON; NITROGEN; etc.; HETEROTROPHY (from organic sources) or AUTOTROPHY (from CARBON DIOXIDE). They can also be classified by whether or not they stain (based on the structure of their CELL WALLS) with CRYSTAL VIOLET dye: gram-negative or gram-positive.Gene Library: A large collection of DNA fragments cloned (CLONING, MOLECULAR) from a given organism, tissue, organ, or cell type. It may contain complete genomic sequences (GENOMIC LIBRARY) or complementary DNA sequences, the latter being formed from messenger RNA and lacking intron sequences.Knee Joint: A synovial hinge connection formed between the bones of the FEMUR; TIBIA; and PATELLA.Mathematical Computing: Computer-assisted interpretation and analysis of various mathematical functions related to a particular problem.Automation: Controlled operation of an apparatus, process, or system by mechanical or electronic devices that take the place of human organs of observation, effort, and decision. (From Webster's Collegiate Dictionary, 1993)Genome, Plant: The genetic complement of a plant (PLANTS) as represented in its DNA.Systems Integration: The procedures involved in combining separately developed modules, components, or subsystems so that they work together as a complete system. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed)Circular Dichroism: A change from planar to elliptic polarization when an initially plane-polarized light wave traverses an optically active medium. (McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed)Neural Networks (Computer): A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.Membrane Proteins: Proteins which are found in membranes including cellular and intracellular membranes. They consist of two types, peripheral and integral proteins. They include most membrane-associated enzymes, antigenic proteins, transport proteins, and drug, hormone, and lectin receptors.Hydrogen Bonding: A low-energy attractive force between hydrogen and another element. It plays a major role in determining the properties of water, proteins, and other compounds.Introns: Sequences of DNA in the genes that are located between the EXONS. They are transcribed along with the exons but are removed from the primary gene transcript by RNA SPLICING to leave mature RNA. Some introns code for separate genes.Evaluation Studies as Topic: Studies determining the effectiveness or value of processes, personnel, and equipment, or the material on conducting such studies. For drugs and devices, CLINICAL TRIALS AS TOPIC; DRUG EVALUATION; and DRUG EVALUATION, PRECLINICAL are available.Escherichia coli Proteins: Proteins obtained from ESCHERICHIA COLI.HMG-Box Domains: DNA-binding domains present in proteins of the HMG-box superfamily including the archetypal HMGB PROTEINS, a number of sequence specific TRANSCRIPTION FACTORS, and other DNA-BINDING PROTEINS. The domains consist of 70-80 amino acids that form an L-shaped fold from three alpha-helical segments. The domain has the capacity to recognize and/or induce specific DNA structures and effect the accessibility of the DNA to other proteins involved in transcription, recombination, or DNA repair. (Note that not all HIGH MOBILITY GROUP PROTEINS contain this domain.)Cattle: Domesticated bovine animals of the genus Bos, usually kept on a farm or ranch and used for the production of meat or dairy products or for heavy labor.Eukaryotic Cells: Cells of the higher organisms, containing a true nucleus bounded by a nuclear membrane.Recombination, Genetic: Production of new arrangements of DNA by various mechanisms such as assortment and segregation, CROSSING OVER; GENE CONVERSION; GENETIC TRANSFORMATION; GENETIC CONJUGATION; GENETIC TRANSDUCTION; or mixed infection of viruses.DNA Mutational Analysis: Biochemical identification of mutational changes in a nucleotide sequence.Oryza sativa: Annual cereal grass of the family POACEAE and its edible starchy grain, rice, which is the staple food of roughly one-half of the world's population.RNA, Bacterial: Ribonucleic acid in bacteria having regulatory and catalytic roles as well as involvement in protein synthesis.Mammals: Warm-blooded vertebrate animals belonging to the class Mammalia, including all that possess hair and suckle their young.Nucleotides: The monomeric units from which DNA or RNA polymers are constructed. They consist of a purine or pyrimidine base, a pentose sugar, and a phosphate group. (From King & Stansfield, A Dictionary of Genetics, 4th ed)DNA Barcoding, Taxonomic: Techniques for standardizing and expediting taxonomic identification or classification of organisms that are based on deciphering the sequence of one or a few regions of DNA known as the "DNA barcode".Saccharomyces cerevisiae: A species of the genus SACCHAROMYCES, family Saccharomycetaceae, order Saccharomycetales, known as "baker's" or "brewer's" yeast. The dried form is used as a dietary supplement.Viral Proteins: Proteins found in any species of virus.Solanaceae: A plant family of the order Solanales, subclass Asteridae. Among the most important are POTATOES; TOMATOES; CAPSICUM (green and red peppers); TOBACCO; and BELLADONNA.Peptides: Members of the class of compounds composed of AMINO ACIDS joined together by peptide bonds between adjacent amino acids into linear, branched or cyclical structures. OLIGOPEPTIDES are composed of approximately 2-12 amino acids. Polypeptides are composed of approximately 13 or more amino acids. PROTEINS are linear polypeptides that are normally synthesized on RIBOSOMES.Synteny: The presence of two or more genetic loci on the same chromosome. Extensions of this original definition refer to the similarity in content and organization between chromosomes, of different species for example.Sequence Deletion: Deletion of sequences of nucleic acids from the genetic material of an individual.Models, Theoretical: Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.Documentation: Systematic organization, storage, retrieval, and dissemination of specialized information, especially of a scientific or technical nature (From ALA Glossary of Library and Information Science, 1983). It often involves authenticating or validating information.Mutagenesis: Process of generating a genetic MUTATION. It may occur spontaneously or be induced by MUTAGENS.National Library of Medicine (U.S.): An agency of the NATIONAL INSTITUTES OF HEALTH concerned with overall planning, promoting, and administering programs pertaining to advancement of medical and related sciences. Major activities of this institute include the collection, dissemination, and exchange of information important to the progress of medicine and health, research in medical informatics and support for medical library development.Mutagenesis, Insertional: Mutagenesis where the mutation is caused by the introduction of foreign DNA sequences into a gene or extragenic sequence. This may occur spontaneously in vivo or be experimentally induced in vivo or in vitro. Proviral DNA insertions into or adjacent to a cellular proto-oncogene can interrupt GENETIC TRANSLATION of the coding sequences or interfere with recognition of regulatory elements and cause unregulated expression of the proto-oncogene resulting in tumor formation.Histidine: An essential amino acid that is required for the production of HISTAMINE.DNA, Ribosomal: DNA sequences encoding RIBOSOMAL RNA and the segments of DNA separating the individual ribosomal RNA genes, referred to as RIBOSOMAL SPACER DNA.Ligands: A molecule that binds to another molecule, used especially to refer to a small molecule that binds specifically to a larger molecule, e.g., an antigen binding to an antibody, a hormone or neurotransmitter binding to a receptor, or a substrate or allosteric effector binding to an enzyme. Ligands are also molecules that donate or accept a pair of electrons to form a coordinate covalent bond with the central metal atom of a coordination complex. (From Dorland, 27th ed)Archaeal Proteins: Proteins found in any species of archaeon.Carrier Proteins: Transport proteins that carry specific substances in the blood or across cell membranes.Imaging, Three-Dimensional: The process of generating three-dimensional images by electronic, photographic, or other methods. For example, three-dimensional images can be generated by assembling multiple tomographic images with the aid of a computer, while photographic 3-D images (HOLOGRAPHY) can be made by exposing film to the interference pattern created when two laser light sources shine on an object.Molecular Conformation: The characteristic three-dimensional shape of a molecule.Prokaryotic Cells: Cells lacking a nuclear membrane so that the nuclear material is either scattered in the cytoplasm or collected in a nucleoid region.Pseudogenes: Genes bearing close resemblance to known genes at different loci, but rendered non-functional by additions or deletions in structure that prevent normal transcription or translation. When lacking introns and containing a poly-A segment near the downstream end (as a result of reverse copying from processed nuclear RNA into double-stranded DNA), they are called processed genes.DNA, Chloroplast: Deoxyribonucleic acid that makes up the genetic material of CHLOROPLASTS.Dimerization: The process by which two molecules of the same chemical composition form a condensation product or polymer.Surgery, Computer-Assisted: Surgical procedures conducted with the aid of computers. This is most frequently used in orthopedic and laparoscopic surgery for implant placement and instrument guidance. Image-guided surgery interactively combines prior CT scans or MRI images with real-time video.Enzymes: Biological molecules that possess catalytic activity. They may occur naturally or be synthetically created. Enzymes are usually proteins, however CATALYTIC RNA and CATALYTIC DNA molecules have also been identified.Models, Biological: Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.Classification: The systematic arrangement of entities in any field into categories classes based on common characteristics such as properties, morphology, subject matter, etc.Transcription Factors: Endogenous substances, usually proteins, which are effective in the initiation, stimulation, or termination of the genetic transcription process.RNA, Ribosomal, 16S: Constituent of 30S subunit prokaryotic ribosomes containing 1600 nucleotides and 21 proteins. 16S rRNA is involved in initiation of polypeptide synthesis.Repetitive Sequences, Nucleic Acid: Sequences of DNA or RNA that occur in multiple copies. There are several types: INTERSPERSED REPETITIVE SEQUENCES are copies of transposable elements (DNA TRANSPOSABLE ELEMENTS or RETROELEMENTS) dispersed throughout the genome. TERMINAL REPEAT SEQUENCES flank both ends of another sequence, for example, the long terminal repeats (LTRs) on RETROVIRUSES. Variations may be direct repeats, those occurring in the same direction, or inverted repeats, those opposite to each other in direction. TANDEM REPEAT SEQUENCES are copies which lie adjacent to each other, direct or inverted (INVERTED REPEAT SEQUENCES).Static Electricity: The accumulation of an electric charge on a objectModels, Structural: A representation, generally small in scale, to show the structure, construction, or appearance of something. (From Random House Unabridged Dictionary, 2d ed)Protein Interaction Mapping: Methods for determining interaction between PROTEINS.Thermodynamics: A rigorously mathematical analysis of energy relationships (heat, work, temperature, and equilibrium). It describes systems whose states are determined by thermal parameters, such as temperature, in addition to mechanical and electromagnetic parameters. (From Hawley's Condensed Chemical Dictionary, 12th ed)Peptide Fragments: Partial proteins formed by partial hydrolysis of complete proteins or generated through PROTEIN ENGINEERING techniques.Plants: Multicellular, eukaryotic life forms of kingdom Plantae (sensu lato), comprising the VIRIDIPLANTAE; RHODOPHYTA; and GLAUCOPHYTA; all of which acquired chloroplasts by direct endosymbiosis of CYANOBACTERIA. They are characterized by a mainly photosynthetic mode of nutrition; essentially unlimited growth at localized regions of cell divisions (MERISTEMS); cellulose within cells providing rigidity; the absence of organs of locomotion; absence of nervous and sensory systems; and an alternation of haploid and diploid generations.Tibia: The second longest bone of the skeleton. It is located on the medial side of the lower leg, articulating with the FIBULA laterally, the TALUS distally, and the FEMUR proximally.Cysteine: A thiol-containing non-essential amino acid that is oxidized to form CYSTINE.Methanococcus: A genus of anaerobic coccoid METHANOCOCCACEAE whose organisms are motile by means of polar tufts of flagella. These methanogens are found in salt marshes, marine and estuarine sediments, and the intestinal tract of animals.Base Composition: The relative amounts of the PURINES and PYRIMIDINES in a nucleic acid.Molecular Structure: The location of the atoms, groups or ions relative to one another in a molecule, as well as the number, type and location of covalent bonds.RNA, Messenger: RNA sequences that serve as templates for protein synthesis. Bacterial mRNAs are generally primary transcripts in that they do not require post-transcriptional processing. Eukaryotic mRNA is synthesized in the nucleus and must be exported to the cytoplasm for translation. Most eukaryotic mRNAs have a sequence of polyadenylic acid at the 3' end, referred to as the poly(A) tail. The function of this tail is not known for certain, but it may play a role in the export of mature mRNA from the nucleus as well as in helping stabilize some mRNA molecules by retarding their degradation in the cytoplasm.Time Factors: Elements of limited time intervals, contributing to particular results or situations.

Intracellular signalling: PDK1--a kinase at the hub of things. (1/38700)

Phosphoinositide-dependent kinase 1 (PDK1) is at the hub of many signalling pathways, activating PKB and PKC isoenzymes, as well as p70 S6 kinase and perhaps PKA. PDK1 action is determined by colocalization with substrate and by target site availability, features that may enable it to operate in both resting and stimulated cells.  (+info)

Molecular phylogeny of the ETS gene family. (2/38700)

We have constructed a molecular phylogeny of the ETS gene family. By distance and parsimony analysis of the ETS conserved domains we show that the family containing so far 29 different genes in vertebrates can be divided into 13 groups of genes namely ETS, ER71, GABP, PEA3, ERG, ERF, ELK, DETS4, ELF, ESE, TEL, YAN, SPI. Since the three dimensional structure of the ETS domain has revealed a similarity with the winged-helix-turn-helix proteins, we used two of them (CAP and HSF) to root the tree. This allowed us to show that the family can be divided into five subfamilies: ETS, DETS4, ELF, TEL and SPI. The ETS subfamily comprises the ETS, ER71, GABP, PEA3, ERG, ERF and the ELK groups which appear more related to each other than to any other ETS family members. The fact that some members of these subfamilies were identified in early metazoans such as diploblasts and sponges suggests that the diversification of ETS family genes predates the diversification of metazoans. By the combined analysis of both the ETS and the PNT domains, which are conserved in some members of the family, we showed that the GABP group, and not the ERG group, is the one most closely related to the ETS group. We also observed that the speed of accumulation of mutations in the various genes of the family is highly variable. Noticeably, paralogous members of the ELK group exhibit strikingly different evolutionary speed suggesting that the evolutionary pressure they support is very different.  (+info)

Crystal structure of MHC class II-associated p41 Ii fragment bound to cathepsin L reveals the structural basis for differentiation between cathepsins L and S. (3/38700)

The lysosomal cysteine proteases cathepsins S and L play crucial roles in the degradation of the invariant chain during maturation of MHC class II molecules and antigen processing. The p41 form of the invariant chain includes a fragment which specifically inhibits cathepsin L but not S. The crystal structure of the p41 fragment, a homologue of the thyroglobulin type-1 domains, has been determined at 2.0 A resolution in complex with cathepsin L. The structure of the p41 fragment demonstrates a novel fold, consisting of two subdomains, each stabilized by disulfide bridges. The first subdomain is an alpha-helix-beta-strand arrangement, whereas the second subdomain has a predominantly beta-strand arrangement. The wedge shape and three-loop arrangement of the p41 fragment bound to the active site cleft of cathepsin L are reminiscent of the inhibitory edge of cystatins, thus demonstrating the first example of convergent evolution observed in cysteine protease inhibitors. However, the different fold of the p41 fragment results in additional contacts with the top of the R-domain of the enzymes, which defines the specificity-determining S2 and S1' substrate-binding sites. This enables inhibitors based on the thyroglobulin type-1 domain fold, in contrast to the rather non-selective cystatins, to exhibit specificity for their target enzymes.  (+info)

A single membrane-embedded negative charge is critical for recognizing positively charged drugs by the Escherichia coli multidrug resistance protein MdfA. (4/38700)

The nature of the broad substrate specificity phenomenon, as manifested by multidrug resistance proteins, is not yet understood. In the Escherichia coli multidrug transporter, MdfA, the hydrophobicity profile and PhoA fusion analysis have so far identified only one membrane-embedded charged amino acid residue (E26). In order to determine whether this negatively charged residue may play a role in multidrug recognition, we evaluated the expression and function of MdfA constructs mutated at this position. Replacing E26 with the positively charged residue lysine abolished the multidrug resistance activity against positively charged drugs, but retained chloramphenicol efflux and resistance. In contrast, when the negative charge was preserved in a mutant with aspartate instead of E26, chloramphenicol recognition and transport were drastically inhibited; however, the mutant exhibited almost wild-type multidrug resistance activity against lipophilic cations. These results suggest that although the negative charge at position 26 is not essential for active transport, it dictates the multidrug resistance character of MdfA. We show that such a negative charge is also found in other drug resistance transporters, and its possible significance regarding multidrug resistance is discussed.  (+info)

Anopheles gambiae Ag-STAT, a new insect member of the STAT family, is activated in response to bacterial infection. (5/38700)

A new insect member of the STAT family of transcription factors (Ag-STAT) has been cloned from the human malaria vector Anopheles gambiae. The domain involved in DNA interaction and the SH2 domain are well conserved. Ag-STAT is most similar to Drosophila D-STAT and to vertebrate STATs 5 and 6, constituting a proposed ancient class A of the STAT family. The mRNA is expressed at all developmental stages, and the protein is present in hemocytes, pericardial cells, midgut, skeletal muscle and fat body cells. There is no evidence of transcriptional activation following bacterial challenge. However, bacterial challenge results in nuclear translocation of Ag-STAT protein in fat body cells and induction of DNA-binding activity that recognizes a STAT target site. In vitro treatment with pervanadate (vanadate and H2O2) translocates Ag-STAT to the nucleus in midgut epithelial cells. This is the first evidence of direct participation of the STAT pathway in immune responses in insects.  (+info)

Assembly requirements of PU.1-Pip (IRF-4) activator complexes: inhibiting function in vivo using fused dimers. (6/38700)

Gene expression in higher eukaryotes appears to be regulated by specific combinations of transcription factors binding to regulatory sequences. The Ets factor PU.1 and the IRF protein Pip (IRF-4) represent a pair of interacting transcription factors implicated in regulating B cell-specific gene expression. Pip is recruited to its binding site on DNA by phosphorylated PU.1. PU.1-Pip interaction is shown to be template directed and involves two distinct protein-protein interaction surfaces: (i) the ets and IRF DNA-binding domains; and (ii) the phosphorylated PEST region of PU.1 and a lysine-requiring putative alpha-helix in Pip. Thus, a coordinated set of protein-protein and protein-DNA contacts are essential for PU.1-Pip ternary complex assembly. To analyze the function of these factors in vivo, we engineered chimeric repressors containing the ets and IRF DNA-binding domains connected by a flexible POU domain linker. When stably expressed, the wild-type fused dimer strongly repressed the expression of a rearranged immunoglobulin lambda gene, thereby establishing the functional importance of PU.1-Pip complexes in B cell gene expression. Comparative analysis of the wild-type dimer with a series of mutant dimers distinguished a gene regulated by PU.1 and Pip from one regulated by PU.1 alone. This strategy should prove generally useful in analyzing the function of interacting transcription factors in vivo, and for identifying novel genes regulated by such complexes.  (+info)

Analysis of two cosmid clones from chromosome 4 of Drosophila melanogaster reveals two new genes amid an unusual arrangement of repeated sequences. (7/38700)

Chromosome 4 from Drosophila melanogaster has several unusual features that distinguish it from the other chromosomes. These include a diffuse appearance in salivary gland polytene chromosomes, an absence of recombination, and the variegated expression of P-element transgenes. As part of a larger project to understand these properties, we are assembling a physical map of this chromosome. Here we report the sequence of two cosmids representing approximately 5% of the polytenized region. Both cosmid clones contain numerous repeated DNA sequences, as identified by cross hybridization with labeled genomic DNA, BLAST searches, and dot matrix analysis, which are positioned between and within the transcribed sequences. The repetitive sequences include three copies of the mobile element Hoppel, one copy of the mobile element HB, and 18 DINE repeats. DINE is a novel, short repeated sequence dispersed throughout both cosmid sequences. One cosmid includes the previously described cubitus interruptus (ci) gene and two new genes: that a gene with a predicted amino acid sequence similar to ribosomal protein S3a which is consistent with the Minute(4)101 locus thought to be in the region, and a novel member of the protein family that includes plexin and met-hepatocyte growth factor receptor. The other cosmid contains only the two short 5'-most exons from the zinc-finger-homolog-2 (zfh-2) gene. This is the first extensive sequence analysis of noncoding DNA from chromosome 4. The distribution of the various repeats suggests its organization is similar to the beta-heterochromatic regions near the base of the major chromosome arms. Such a pattern may account for the diffuse banding of the polytene chromosome 4 and the variegation of many P-element transgenes on the chromosome.  (+info)

The mouse Aire gene: comparative genomic sequencing, gene organization, and expression. (8/38700)

Mutations in the human AIRE gene (hAIRE) result in the development of an autoimmune disease named APECED (autoimmune polyendocrinopathy candidiasis ectodermal dystrophy; OMIM 240300). Previously, we have cloned hAIRE and shown that it codes for a putative transcription-associated factor. Here we report the cloning and characterization of Aire, the murine ortholog of hAIRE. Comparative genomic sequencing revealed that the structure of the AIRE gene is highly conserved between human and mouse. The conceptual proteins share 73% homology and feature the same typical functional domains in both species. RT-PCR analysis detected three splice variant isoforms in various mouse tissues, and interestingly one isoform was conserved in human, suggesting potential biological relevance of this product. In situ hybridization on mouse and human histological sections showed that AIRE expression pattern was mainly restricted to a few cells in the thymus, calling for a tissue-specific function of the gene product.  (+info)

Core column prediction for protein multiple sequence alignments | Algorithms for Molecular Biology | Full TextCore column prediction for protein multiple sequence alignments | Algorithms for Molecular Biology | Full Text
In a computed protein multiple sequence alignment, the coreness of a column is the fraction of its substitutions that are in so-called core columns of the gold-standard reference alignment of its proteins. In benchmark suites of protein reference alignments, the core columns of the reference alignment are those that can be confidently labeled as correct, usually due to all residues in the column being sufficiently close in the spatial superposition of the known three-dimensional structures of the proteins. Typically the accuracy of a protein multiple sequence alignment that has been computed for a benchmark is only measured with respect to the core columns of the reference alignment. When computing an alignment in practice, however, a reference alignment is not known, so the coreness of its columns can only be predicted. We develop for the first time a predictor of column coreness for protein multiple sequence alignments. This allows us to predict which columns of a computed alignment are core, and
ClustalXeed : a GUI-based grid computation version for high performance and terabyte size multiple sequence alignment | BMC...ClustalXeed : a GUI-based grid computation version for high performance and terabyte size multiple sequence alignment | BMC...
There is an increasing demand to assemble and align large-scale biological sequence data sets. The commonly used multiple sequence alignment programs are still limited in their ability to handle very large amounts of sequences because the system lacks a scalable high-performance computing (HPC) environment with a greatly extended data storage capacity. We designed ClustalXeed, a software system for multiple sequence alignment with incremental improvements over previous versions of the ClustalX and ClustalW-MPI software. The primary advantage of ClustalXeed over other multiple sequence alignment software is its ability to align a large family of protein or nucleic acid sequences. To solve the conventional memory-dependency problem, ClustalXeed uses both physical random access memory (RAM) and a distributed file-allocation system for distance matrix construction and pair-align computation. The computation efficiency of disk-storage system was markedly improved by implementing an efficient load-balancing
Assessing the efficiency of multiple sequence alignment programs | Algorithms for Molecular Biology | Full TextAssessing the efficiency of multiple sequence alignment programs | Algorithms for Molecular Biology | Full Text
Multiple sequence alignment (MSA) is an extremely useful tool for molecular and evolutionary biology and there are several programs and algorithms available for this purpose. Although previous studies have compared the alignment accuracy of different MSA programs, their computational time and memory usage have not been systematically evaluated. Given the unprecedented amount of data produced by next generation deep sequencing platforms, and increasing demand for large-scale data analysis, it is imperative to optimize the application of software. Therefore, a balance between alignment accuracy and computational cost has become a critical indicator of the most suitable MSA program. We compared both accuracy and cost of nine popular MSA programs, namely CLUSTALW, CLUSTAL OMEGA, DIALIGN-TX, MAFFT, MUSCLE, POA, Probalign, Probcons and T-Coffee, against the benchmark alignment dataset BAliBASE and discuss the relevance of some implementations embedded in each programs algorithm. Accuracy of alignment was
MISHIMA - a new method for high speed multiple alignment of nucleotide sequences of bacterial genome scale data | BMC...MISHIMA - a new method for high speed multiple alignment of nucleotide sequences of bacterial genome scale data | BMC...
Large nucleotide sequence datasets are becoming increasingly common objects of comparison. Complete bacterial genomes are reported almost everyday. This creates challenges for developing new multiple sequence alignment methods. Conventional multiple alignment methods are based on pairwise alignment and/or progressive alignment techniques. These approaches have performance problems when the number of sequences is large and when dealing with genome scale sequences. We present a new method of multiple sequence alignment, called MISHIMA (Method for Inferring Sequence History In terms of Multiple Alignment), that does not depend on pairwise sequence comparison. A new algorithm is used to quickly find rare oligonucleotide sequences shared by all sequences. Divide and conquer approach is then applied to break the sequences into fragments that can be aligned independently by an external alignment program. These partial alignments are assembled together to form a complete alignment of the original sequences.
Sequence AlignmentSequence Alignment
CLUSTAL-W is currently one of the most popular automated multiple sequence alignment tools. CLUSTAL-W calculates a distance matrix for the sequences that are to be aligned. The distance matrix is then used to generate a phylogenetic tree that is used to guide the series of global alignments needed to create the multiple alignment. This is referred to as progressive alignment. Mutliple sequence alignments may also be created by hand and involve gapped or ungapped sequences. Typically, gapped alignments are used for full protein sequences, whereas ungapped alignments may be used to identify protein domains or motifs (See BLOCKS database).. Other multiple sequence alignment methods include DIALIGN, T-Coffee, and POA (Lassman and Sonnhammer, 2002).. ...
Protein and RNA multiple sequence alignment, protein secondary structure prediction, trees, sub-family and function analysis...Protein and RNA multiple sequence alignment, protein secondary structure prediction, trees, sub-family and function analysis...
Jalview hands-on training course is for anyone who works with sequence data and multiple sequence alignments from proteins, RNA and DNA.. Register via the University of Cambridge website.. Jalview is free software for protein and nucleic acid sequence alignment generation, visualisation and analysis. It includes sophisticated editing options and provides a range of analysis tools to investigate the structure and function of macromolecules through a multiple window interface. For example, Jalview supports 8 popular methods for multiple sequence alignment, prediction of protein secondary structure by JPred and disorder prediction by four methods. Jalview also has options to generate phylogenetic trees, and assess consensus and conservation across sequence families. Sequences, alignments and additional annotation can be accessed directly from public databases and journal-quality figures generated for publication.. The course involves of a mixture of talks and hands-on exercises.. Day 1 is an ...
Serval - T-Coffee: a web server for the multiple sequence alignment of protein and RNA sequences using structural information...Serval - T-Coffee: a web server for the multiple sequence alignment of protein and RNA sequences using structural information...
This article introduces a new interface for T-Coffee, a consistency-based multiple sequence alignment program. This interface provides an easy and intuitive access to the most popular functionality of the package. These include the default T-Coffee mode for protein and nucleic acid sequences, the M-Coffee mode that allows combining the output of any other aligners, and template-based modes of T-Coffee that deliver high accuracy alignments while using structural or homology derived templates. These three available template modes are Expresso for the alignment of protein with a known 3D-Structure, R-Coffee to align RNA sequences with conserved secondary structures and PSI-Coffee to accurately align distantly related sequences using homology extension. The new server benefits from recent improvements of the T-Coffee algorithm and can align up to 150 sequences as long as 10,000 residues and is available from both http://www.tcoffee.org and its main mirror http://tcoffee.crg.cat.
MAFFT multiple sequence alignment software version 7: improvements in performance and usabilityMAFFT multiple sequence alignment software version 7: improvements in performance and usability
We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were im …
Grouping of amino acid types and extraction of amino acid properties from multiple sequence alignments using variance...Grouping of amino acid types and extraction of amino acid properties from multiple sequence alignments using variance...
TY - JOUR. T1 - Grouping of amino acid types and extraction of amino acid properties from multiple sequence alignments using variance maximization. AU - Wrabl, James O.. AU - Grishin, Nick V.. PY - 2005/11/15. Y1 - 2005/11/15. N2 - Understanding of amino acid type co-occurrence in trusted multiple sequence alignments is a prerequisite for improved sequence alignment and remote homology detection algorithms. Two objective approaches were used to investigate co-occurrence, both based on variance maximization of the weighted residue frequencies in columns taken from a large alignment database. The first approach discretely grouped amino acid types, and the second approach extracted orthogonal properties of amino acids using principal components analysis. The grouping results corresponded to amino acid physical properties such as side chain hydrophobicity, size, or backbone flexibility, and an optimal arrangement of approximately eight groups was observed. However, interpretation of the orthogonal ...
CombAlign: a code for generating a one-to-many sequence alignment from a set of pairwise structure-based sequence alignments |...CombAlign: a code for generating a one-to-many sequence alignment from a set of pairwise structure-based sequence alignments |...
CombAlign is a new Python code that generates a gapped, multiple structure-based sequence alignment (MSSA) given a set of pairwise structure-based sequence alignments. CombAlign has utility in assisting the user in distinguishing structurally conserved versus divergent regions on a reference protein structure relative to other closely related structures. The method for combining multiple pairwise alignments is straightforward, involving the recording of pre-computed residue-residue correspondences between positions on the reference protein and each compared structure, and insertion of non-redundant gaps, as needed, to reflect amino-acid deletions or structural divergence in the reference relative to one or more compared structures.. CombAlign is not intended for use in applications for which greater benefit would be provided using a multiple structure alignment as generated by the vast majority of open-source programs [20], nor does it propose to address matters of protein evolution or function ...
ALL | EMBOSS, a sequence alignment softwareALL | EMBOSS, a sequence alignment software
ALL is a high speed, large data set sequence alignment tool for Pairwise sequence alignment and Multiple Sequence Alignment (MSA). This tool processes both Protein and Nucleotide local sequence alignments. The type of sequence is automatically recognized. Any printable character set can be used except reserved characters.
Large Grain Size Stochastic Optimization Alignment by Hyrum Carroll, Mark J. Clement et al."Large Grain Size Stochastic Optimization Alignment" by Hyrum Carroll, Mark J. Clement et al.
DNA sequence alignment is a critical step in identifying homology between organisms. The most widely used alignment program, ClustalW, is known to suffer from the local minima problem, where suboptimal guide trees produce incorrect gap insertions. The optimization alignment approach, has been shown to be effective in combining alignment and phylogenetic search in order to avoid the problems associated with poor guide trees. The optimization alignment algorithm operates at a small grain size, aligning each tree found, wasting time producing multiple sequence alignments for suboptimal trees. This research develops and analyzes a large grain size algorithm for optimization alignment that iterates through steps of alignment and phylogeny search, thus improving the quality of guide trees used for computation of multiple sequence alignments and eliminating computation of multiple sequence alignments for sub-optimal guide trees. Local minima are avoided by the use of stochastic search methods. Large Grain Size
Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega | Molecular Systems BiologyFast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega | Molecular Systems Biology
Multiple sequence alignments (MSAs) are essential in most bioinformatics analyses that involve comparing homologous sequences. The exact way of computing an optimal alignment between N sequences has a computational complexity of O(LN) for N sequences of length L making it prohibitive for even small numbers of sequences. Most automatic methods are based on the progressive alignment heuristic (Hogeweg and Hesper, 1984), which aligns sequences in larger and larger subalignments, following the branching order in a guide tree. With a complexity of roughly O(N2), this approach can routinely make alignments of a few thousand sequences of moderate length, but it is tough to make alignments much bigger than this. The progressive approach is a greedy algorithm where mistakes made at the initial alignment stages cannot be corrected later. To counteract this effect, the consistency principle was developed (Notredame et al, 2000). This has allowed the production of a new generation of more accurate ...
Downloading multiple sequence alignment as clustal format file from clustal omega.Downloading multiple sequence alignment as clustal format file from clustal omega.
Hi. Ive been trying to download a multiple sequence alignment from clustal omega as a clustal format file, but whenever I click on the download option, it just opens a new page with only the alignments displayed. I tried downloading the page as a .pdf file and converting it into rtf, but that destroys the formatting. Same thing with simply copy/pasting into a text file. I need a clustal formatted file for use with PriFi ( for designing primers from multiple sequence alignment ). Is there any workaround to this. Or is there something else I can use that does the MSA and the primer design from a multiple sequence fast file. (im using mac os x mavericks ) ...
Structural alignment software - WikipediaStructural alignment software - Wikipedia
This list of structural comparison and alignment software is a compilation of software tools and web portals used in pairwise or multiple structural comparison and structural alignment. Key map: Class: Cα -- Backbone Atom (Cα) Alignment; AllA -- All Atoms Alignment; SSE -- Secondary Structure Elements Alignment; Seq -- Sequence-based alignment Pair -- Pairwise Alignment (2 structures *only*); Multi -- Multiple Structure Alignment (MStA); C-Map -- Contact Map Surf -- Connolly Molecular Surface Alignment SASA -- Solvent Accessible Surface Area Dihed -- Dihedral Backbone Angles PB -- Protein Blocks Flexible: No -- Only rigid-body transformations are considered between the structures being compared. Yes -- The method allows for some flexibility within the structures being compared, such as movements around hinge regions. Aung, Zeyar; Kian-Lee Tan (Dec 2006). "MatAlign: Precise protein structure comparison by matrix alignment". Journal of Bioinformatics and Computational Biology. 4 (6): 1197-216. ...
FSA For Linux 1.15.6 - FSA is a probabilistic multiple sequence alignment algorithm which uses a...FSA For Linux 1.15.6 - FSA is a probabilistic multiple sequence alignment algorithm which uses a...
FSA is a probabilistic multiple sequence alignment algorithm which uses a distancebased approach to aligning homologous protein RNA or DNA sequences
Predicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques - TechyLibPredicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques - TechyLib
document titled Predicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques is about AI and Robotics
Scientific Protocols - A bioinformatics protocol for rigorous structure-based sequence alignment of distantly related...Scientific Protocols - A bioinformatics protocol for rigorous structure-based sequence alignment of distantly related...
Accurate sequence alignments of distantly related proteins are crucial for the better understanding of proteins at their family/superfamily level. However, such alignments of distantly related proteins are often hard to obtain by automatic multiple sequence alignment programs. Hence, we suggest a protocol that permits the reliable sequence alignment of distantly related proteins whose structural information is available. This protocol employs two stages of structure-based sequence alignments in order to obtain reliable alignments. The method proposed is clearly suited to work for protein structural members with distant relationships. We further propose a novel assessment of the derived alignments using the measurements of the structural variations and the percentage secondary structural equivalences. This structure-based sequence alignment protocol can be employed for a single superfamily or for a large number of structural domain superfamilies in a near-automatic and rapid manner.. Development ...
High performance biological pairwise sequence alignment: FPGA versus GPU versus cell BE versus GPP<...High performance biological pairwise sequence alignment: FPGA versus GPU versus cell BE versus GPP<...
TY - JOUR. T1 - High performance biological pairwise sequence alignment. T2 - FPGA versus GPU versus cell BE versus GPP. AU - Benkrid, Khaled. AU - Akoglu, Ali. AU - Ling, Cheng. AU - Song, Yang. AU - Liu, Ying. AU - Tian, Xiang. PY - 2012. Y1 - 2012. N2 - This paper explores the pros and cons of reconfigurable computing in the form of FPGAs for high performance efficient computing. In particular, the paper presents the results of a comparative study between three different acceleration technologies, namely, Field Programmable Gate Arrays (FPGAs), Graphics Processor Units (GPUs), and IBMs Cell Broadband Engine (Cell BE), in the design and implementation of the widely-used Smith-Waterman pairwise sequence alignment algorithm, with general purpose processors as a base reference implementation. Comparison criteria include speed, energy consumption, and purchase and development costs. The study shows that FPGAs largely outperform all other implementation platforms on performance per watt criterion ...
MSAProbs: Multiple Sequence Alignment download | SourceForge.netMSAProbs: Multiple Sequence Alignment download | SourceForge.net
Download MSAProbs: Multiple Sequence Alignment for free. One of the most accurate multiple protein sequence aligners. MSAProbs is an open-source protein multiple sequence ailgnment algorithm, achieving the stastistically highest alignment accuracy on popular benchmarks: BALIBASE, PREFAB, SABMARK, OXBENCH, compared to ClustalW, MAFFT, MUSCLE, ProbCons and Probalign.
ClustalParser: Libary for parsing Clustal tools outputClustalParser: Libary for parsing Clustal tools output
Currently contains parsers and datatypes for: clustalw2, clustalo, mlocarna, cmalign. Clustal tools are multiple sequence alignment tools for biological sequences like DNA, RNA and Protein. For more information on clustal Tools refer to http://www.clustal.org/.. Mlocarna is a multiple sequence alignment tool for RNA sequences with secondary structure output. For more information on mlocarna refer to http://www.bioinf.uni-freiburg.de/Software/LocARNA/.. cmalign is a multiple sequence alignment program based on RNA family models and produces ,among others, clustal output. It is part of infernal http://infernal.janelia.org/.. 4 types of output are parsed. ...
DNA sequence alignment viewers | Next-generation sequencing analysis - omicXDNA sequence alignment viewers | Next-generation sequencing analysis - omicX
Multiple sequence alignment remains a crucial method for understanding the function of groups of related nucleic acid and protein sequences. However, it is known that automatic multiple sequence alignments can often be improved by manual editing. Therefore, tools are needed to view and edit multiple sequence alignments.
Phylogeny-Aware Gap Placement Prevents Errors in Sequence Alignment and Evolutionary Analysis | SciencePhylogeny-Aware Gap Placement Prevents Errors in Sequence Alignment and Evolutionary Analysis | Science
Genetic sequence alignment is the basis of many evolutionary and comparative studies, and errors in alignments lead to errors in the interpretation of evolutionary information in genomes. Traditional multiple sequence alignment methods disregard the phylogenetic implications of gap patterns that they create and infer systematically biased alignments with excess deletions and substitutions, too few insertions, and implausible insertion-deletion-event histories. We present a method that prevents these systematic errors by recognizing insertions and deletions as distinct evolutionary events. We show theoretically and practically that this improves the quality of sequence alignments and downstream analyses over a wide range of realistic alignment problems. These results suggest that insertions and sequence turnover are more common than is currently thought and challenge the conventional picture of sequence evolution and mechanisms of functional and structural changes.. ...
Evaluation Measures of Multiple Sequence Alignments | SciweaversEvaluation Measures of Multiple Sequence Alignments | Sciweavers
Evaluation Measures of Multiple Sequence Alignments - Multiple sequence alignments (MSAs) are frequently used in the study of families of protein sequences or DNA/RNA sequences. They are a fundamental tool for the understanding of the structure, functionality and, ultimately, the evolution of proteins. A new algorithm, the Circular Sum (CS) method, is presented for formally evaluating the quality of an MSA. It is based on the use of a solution to the Traveling Salesman Problem, which identi es a circular tour through an evolutionary tree connecting the sequences in a protein family. With this approach, the calculation of an evolutionary tree and the errors that it would introduce can be avoided altogether. The algorithm gives an upper bound, the best score that can possibly be achieved by any MSA for a given set of protein sequences. Alternatively, if presented with a speci c MSA, the algorithm provides a formal score for the MSA, which serves as an absolute measure of the quality of the MSA. The CS
Multiple sequence alignment - WikipediaMultiple sequence alignment - Wikipedia
The necessary use of heuristics for multiple alignment means that for an arbitrary set of proteins, there is always a good chance that an alignment will contain errors. For example, an evaluation of several leading alignment programs using the BAliBase benchmark found that at least 24% of all pairs of aligned amino acids were incorrectly aligned.[38] These errors can arise because of unique insertions into one or more regions of sequences, or through some more complex evolutionary process leading to proteins that do not align easily by sequence alone. As the number of sequence and their divergence increases many more errors will be made simply because of the heuristic nature of MSA algorithms. Multiple sequence alignment viewers enable alignments to be visually reviewed, often by inspecting the quality of alignment for annotated functional sites on two or more sequences. Many also enable the alignment to be edited to correct these (usually minor) errors, in order to obtain an optimal curated ...
Multiple sequence alignment for short sequences | Haldanes SieveMultiple sequence alignment for short sequences | Haldane's Sieve
Multiple sequence alignment for short sequences Kristóf Takács Multiple sequence alignment (MSA) has been one of the most important problems in bioinformatics for more decades and it is still heavily examined by many mathematicians and biologists. However, mostly because of the practical motivation of this problem, the research on this topic is focused on aligning…
Identification of regions in multiple sequence alignments thermodynamically suitable for targeting by consensus...Identification of regions in multiple sequence alignments thermodynamically suitable for targeting by consensus...
Identification of regions in multiple sequence alignments thermodynamically suitable for targeting by consensus oligonucleotides: application to HIV genome - Background: Computer programs for the generation of multiple sequence alignments such as Clustal W allow detection of regions that are most conserved among many sequence variants. However, even for regions that are equally conserved, their potential utility as hybridization targets varies. Mismatches in sequence variants are more disruptive in some duplexes than in others. Additionally, the propensity for self-interactions amongst oligonucleotides targeting conserved regions differs and the structure of target regions themselves can also influence hybridization efficiency. There is a need to develop software that will employ thermodynamic selection criteria for finding optimal hybridization targets in related sequences. Results: A new scheme and new software for optimal detection of oligonucleotide hybridization targets common to families of
Chapter 6: Multiple Sequence Alignment | Pevsner LabChapter 6: Multiple Sequence Alignment | Pevsner Lab
This page offers the web documents that are referred to in Chapter 6. In Chapter 3 we discussed pairwise alignment, and then in Chapters 4 and 5 we described how a protein or DNA query can be compared to a database. This chapter covers a series of approaches to multiple sequence alignment, including the popular method of progressive alignment and new methods such as consistency-based and structure-based alignment. We also discuss ways to multiply align long segments of genomic DNA. ...
Bio::Tools::Run::Alignment::TCoffee - Object for the calculation of a multiple sequence alignment from a set of unaligned...Bio::Tools::Run::Alignment::TCoffee - Object for the calculation of a multiple sequence alignment from a set of unaligned...
Object for the calculation of a multiple sequence alignment from a set of unaligned sequences or alignments using the TCoffee program
Automatic extraction of reliable regions from multiple sequence alignments - Timo, Sonnhammer, - Knowledge - DocumentsAutomatic extraction of reliable regions from multiple sequence alignments - Timo, Sonnhammer, - Knowledge - Documents
Automatic extraction of reliable regions from multiple sequence alignments : High quality multiple alignments are crucial in the transfer of annotation from one genome to another. Multiple alignment methods strive to achieve ever increasing levels of average accuracy on benchmark sets while the accuracy of individual alignments is often overlooked. Results We have previously developed a method to automatically assess the accuracy and overall difficulty of multiple
3DCoffee@igs: a web server for combining sequences and structures into a multiple sequence alignment | Bioinformatics and...[email protected]: a web server for combining sequences and structures into a multiple sequence alignment | Bioinformatics and...
This paper presents [email protected], a web-based tool dedicated to the computation of high-quality multiple sequence alignments (MSAs). 3D-Coffee makes it possible to mix protein sequences and structures in order to increase the accuracy of the alignments. Structures can be either provided as PDB identifiers or directly uploaded into the server. Given a set of sequences and structures, pairs of structures are aligned with SAP while sequence-structure pairs are aligned with Fugue. The resulting collection of pairwise alignments is then combined into an MSA with the T-Coffee algorithm. The server and its documentation are available from http://igs-server.cnrs-mrs.fr/Tcoffee/.. ...
Advanced Workshop: NIH CMM 1/01Advanced Workshop: NIH CMM 1/01
Announcement: This hands-on computer workshop is designed for people having previous experience with macromolecular visualization in any of the many software packages available. It will focus on the capabilities of Protein Explorer and Chemscape Chime, targeting interests expressed by the participants. Topics may include how to use an automated interface for detailed exploration of noncovalent bonds (the Noncovalent Bond Finder); finding energetically significant cation-pi interactions; generating overviews of noncovalent interactions using "contact surface" displays; how to animate functional conformational changes or movements, such as the binding of calcium to an EF-hand; searching for proteins with similar structures (regardless of sequence) and viewing the resulting structure alignments. We may also create multiple protein sequence alignments and color 3D proteins by conservation and mutation frequency. (If you already have some multiple protein sequence alignments, bring them in FASTA/PIR ...
PROBCONS: Probabilistic Consistency-based Multiple Alignment of Amino Acid SequencesPROBCONS: Probabilistic Consistency-based Multiple Alignment of Amino Acid Sequences
PROBCONS is an efficient protein multiple sequence alignment program, which has demonstrated a statistically significant improvement in accuracy compared to several leading alignment tools ...
SinicView: A visualization environment for comparisons of multiple nucleotide sequence alignment tools<...SinicView: A visualization environment for comparisons of multiple nucleotide sequence alignment tools<...
TY - JOUR. T1 - SinicView. T2 - A visualization environment for comparisons of multiple nucleotide sequence alignment tools. AU - Shih, Arthur Chun Chieh. AU - Lee, D. T.. AU - Lin, Laurent. AU - Peng, Chin Lin. AU - Chen, Shiang Heng. AU - Wu, Yu Wei. AU - Wong, Chun Yi. AU - Chou, Meng Yuan. AU - Shiao, Tze Chang. AU - Hsieh, Mu Fen. PY - 2006/3/2. Y1 - 2006/3/2. N2 - Background: Deluged by the rate and complexity of completed genomic sequences, the need to align longer sequences becomes more urgent, and many more tools have thus been developed. In the initial stage of genomic sequence analysis, a biologist is usually faced with the questions of how to choose the best tool to align sequences of interest and how to analyze and visualize the alignment results, and then with the question of whether poorly aligned regions produced by the tool are indeed not homologous or are just results due to inappropriate alignment tools or scoring systems used. Although several systematic evaluations of ...
Inferred from Sequence Alignment (ISA) - GO WikiInferred from Sequence Alignment (ISA) - GO Wiki
Sequence similarity with experimentally characterized gene products, as determined by alignments, either pairwise or multiple (tools such as BLAST, ClustalW, MUSCLE). An entry in the with field is mandatory. The ISA code is a sub-category of the ISS code. It should be used whenever a sequence alignment is the basis for making an annotation, but only when a curator has manually reviewed the alignment and choice of GO term or if the information is in a published paper, the authors have manually reviewed the evidence. Such alignments may be pairwise alignments (the alignment of two sequences to one another) or multiple alignments (the alignment of 3 or more sequences to one another). BLAST produces pairwise alignments and any annotations based solely on the evaluation of BLAST results should use this code. GO policy states that in order to assert that a query protein has the same function as a match protein, the match protein MUST be experimentally characterized. This prevents transitive annotation ...
Post-processing long sequence alignments • Algorithmic Bioinformatics (ABI) • Department of Mathematics and Computer SciencePost-processing long sequence alignments • Algorithmic Bioinformatics (ABI) • Department of Mathematics and Computer Science
Description:. An X-drop within an alignment, where X,0, is a region of consecutive columns scoring less than -X. Alignments containing no such X-drop are called X-alignments. Obviously, X-alignments avoid the first problem that local alignments contain internal segments scoring less than -X. A normal alignment is an alignment where each prefix or suffix has a non-negative score. Such an alignment is called maximal if it is not contained in any longer normal alignment. Maximal normal alignments clearly avoid the second problem that an entire alignment scores less than a prefix or suffix. The algorithm proposed by Zhang et al. constructs a tree that allows to decompose an alignment into all X-full subalignments where X-full refers to subalignments that are maximal normal alignments and X-alignments. The tree encodes all X-full alignments for all X greater or equal to 0. Hence, the decomposition corresponding to any particular value of X can be readily extracted from the tree. The goal of this ...
Multiple Sequence Alignment - Appending To An AlignmentMultiple Sequence Alignment - Appending To An Alignment
I have a set of 520 influenza sequences for which I have already done multiple sequence alignment, and computed the pairwise identity matrix. If Id like to add in another sequence, I have to re-align everything, and recompute the entire PWI matrix. Is there any program I can use to "append" this other sequence to the alignment, and only compute the PWI w.r.t. every other sequence?. A simple example would be as follows. I have a 2x2 alignment, with the following scores.. ...
Fold assembly of small proteins using monte carlo simulations driven by restraints derived from multiple sequence alignments |...Fold assembly of small proteins using monte carlo simulations driven by restraints derived from multiple sequence alignments |...
The feasibility of predicting the global fold of small proteins by incorporating predicted secondary and tertiary restraints into ab initio folding simulations has been demonstrated on a test set comprised of 20 non-homologous proteins, of which one was a blind prediction of target 42 in the recent CASP2 contest. These proteins contain from 37 to 100 residues and represent all secondary structural classes and a representative variety of global topologies. Secondary structure restraints are provided by the PHD secondary structure prediction algorithm that incorporates multiple sequence information. Predicted tertiary restraints are derived from multiple sequence alignments via a two-step process. First, seed side-chain contacts are identified from correlated mutation analysis, and then a threading-based algorithm is used to expand the number of these seed contacts. A lattice-based reduced protein model and a folding algorithm designed to incorporate these predicted restraints is described. ...
Wikiomics:Multiple sequence alignment - OpenWetWareWikiomics:Multiple sequence alignment - OpenWetWare
Template:Text-needed See also Wikiomics:Bioinfo_tutorial#Protein_Alignment Multiple sequence alignment is widely used in the sequence analysis. It is more reliable, and hosts more information than derived from BLAST multiple pairwise alignment. The MSA allows for identification of common regions between proteins (including motifs), finding conserved residues and analysis of evolutionary relationships between sequences. ...
discomark: nuclear marker discovery from orthologous sequences using draft genome data | Metadiscomark: nuclear marker discovery from orthologous sequences using draft genome data | Meta
High-throughput sequencing has laid the foundation for fast and cost-effective development of phylogenetic markers. Here we present the program discomark, which streamlines the development of nuclear DNA (nDNA) markers from whole-genome (or whole-transcriptome) sequencing data, combining local alignment, alignment trimming, reference mapping and primer design based on multiple sequence alignments to design primer pairs from input orthologous sequences. To demonstrate the suitability of discomark, we designed markers for two groups of species, one consisting of closely related species and one group of distantly related species. For the closely related members of the species complex of Cloeon dipterum s.l. (Insecta, Ephemeroptera), the program discovered a total of 78 markers. Among these, we selected eight markers for amplification and Sanger sequencing. The exon sequence alignments (2526 base pairs) were used to reconstruct a well-supported phylogeny and to infer clearly structured haplotype ...
MUSCLE: a multiple sequence alignment method with reduced time and space complexity | BMC Bioinformatics | Full TextMUSCLE: a multiple sequence alignment method with reduced time and space complexity | BMC Bioinformatics | Full Text
In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUSCLE to achieve the highest scores reported to date on four alignment accuracy benchmarks. Here we present a more complete discussion of the algorithm, describing several previously unpublished techniques that improve biological accuracy and / or computational complexity. We introduce a new option, MUSCLE-fast, designed for high-throughput applications. We also describe a new protocol for evaluating objective functions that align two profiles. We compare the speed and accuracy of MUSCLE with CLUSTALW, Progressive POA and the MAFFT script FFTNS1, the fastest previously published program known to the author. Accuracy is measured using four benchmarks: BAliBASE, PREFAB, SABmark and SMART. We test three variants that offer highest accuracy (MUSCLE with default settings), highest speed (MUSCLE-fast), and a carefully chosen compromise between the
A simple genetic algorithm for multiple sequence alignment. - Semantic ScholarA simple genetic algorithm for multiple sequence alignment. - Semantic Scholar
Multiple sequence alignment plays an important role in molecular sequence analysis. An alignment is the arrangement of two (pairwise alignment) or more (multiple alignment) sequences of residues (nucleotides or amino acids) that maximizes the similarities between them. Algorithmically, the problem consists of opening and extending gaps in the sequences to maximize an objective function (measurement of similarity). A simple genetic algorithm was developed and implemented in the software MSA-GA. Genetic algorithms, a class of evolutionary algorithms, are well suited for problems of this nature since residues and gaps are discrete units. An evolutionary algorithm cannot compete in terms of speed with progressive alignment methods but it has the advantage of being able to correct for initially misaligned sequences; which is not possible with the progressive method. This was shown using the BaliBase benchmark, where Clustal-W alignments were used to seed the initial population in MSA-GA, improving outcome.
MSAViewer: interactive JavaScript visualization of multiple sequence alignments. | ROSTLAB.ORGMSAViewer: interactive JavaScript visualization of multiple sequence alignments. | ROSTLAB.ORG
The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is web ready: written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components.. AVAILABILITY AND IMPLEMENTATION: The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/Supplementary information: Supplementary data are available at Bioinformatics online.. CONTACT: [email protected] ...
MSAViewer: interactive JavaScript visualization of multiple sequence alignments. | ROSTLAB.ORGMSAViewer: interactive JavaScript visualization of multiple sequence alignments. | ROSTLAB.ORG
The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is web ready: written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components.. AVAILABILITY AND IMPLEMENTATION: The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/Supplementary information: Supplementary data are available at Bioinformatics online.. CONTACT: [email protected] ...
python-biopython 1.54-1, Mafft 8py source.htmlpython-biopython 1.54-1, Mafft 8py source.html
Copyright 2009 by Cymon J. Cox. All rights reserved. # This code is part of the Biopython distribution and governed by its # license. Please see the LICENSE file that should have been included # as part of this package. Command line wrapper for the multiple alignment programme MAFFT. http://align.bmr.kyushu-u.ac.jp/mafft/software/ Citations: Katoh, Toh (BMC Bioinformatics 9:212, 2008) Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework (describes RNA structural alignment methods) Katoh, Toh (Briefings in Bioinformatics 9:286-298, 2008) Recent developments in the MAFFT multiple sequence alignment program (outlines version 6) Katoh, Toh (Bioinformatics 23:372-374, 2007) Errata PartTree: an algorithm to build an approximate tree from a large number of unaligned sequences (describes the PartTree algorithm) Katoh, Kuma, Toh, Miyata (Nucleic Acids Res. 33:511-518, 2005) MAFFT version 5: improvement in accuracy of multiple sequence ...
An Application of the ABS LX Algorithm to Multiple Sequence Alignment - Iranian Journal of Operations ResearchAn Application of the ABS LX Algorithm to Multiple Sequence Alignment - Iranian Journal of Operations Research
We present an application of ABS algorithms for multiple sequence alignment (MSA). The Markov decision process (MDP) based model leads to a linear programming problem (LPP), whose solution is linked to a suggested alignment. The important features of our work include the facility of alignment of multiple sequences simultaneously and no limit ...
Large multiple sequence alignments with a root-to-leaf regressive method | Nature BiotechnologyLarge multiple sequence alignments with a root-to-leaf regressive method | Nature Biotechnology
Multiple sequence alignments (MSAs) are used for structural1,2 and evolutionary predictions1,2, but the complexity of aligning large datasets requires the use of approximate solutions3, including the progressive algorithm4. Progressive MSA methods start by aligning the most similar sequences and subsequently incorporate the remaining sequences, from leaf to root, based on a guide tree. Their accuracy declines substantially as the number of sequences is scaled up5. We introduce a regressive algorithm that enables MSA of up to 1.4 million sequences on a standard workstation and substantially improves accuracy on datasets larger than 10,000 sequences. Our regressive algorithm works the other way around from the progressive algorithm and begins by aligning the most dissimilar sequences. It uses an efficient divide-and-conquer strategy to run third-party alignment methods in linear time, regardless of their original complexity. Our approach will enable analyses of extremely large genomic datasets such as the
PhD & Postgrad Sequence Alignment and Analysis Training Workshop | jalview.orgPhD & Postgrad Sequence Alignment and Analysis Training Workshop | jalview.org
1) Multiple Sequence Alignment and Analysis with Jalview on Thursday 23rd November 2017. Day 1 workshop employs talks and hands-on exercises to help students learn to use Jalview, a versatile protein and nucleic acid sequence alignment and analysis tool developed within the School of Life Sciences. We will cover launching Jalview, accessing sequence, alignment and 3D structure databases, creating, editing and analysing alignments, phylogenetic trees, analysing alignments with 3D structures, and preparation of figures for presentation and publication.. Workshop trainer: Dr Jim Procter and Dr Suzanne Duce. (2) Protein Sequence Analysis on Thursday 30th November 2017. Day 2 workshop aims to give an understanding of how best to use computational methods to "make sense" of the structure and function of your favourite protein. The workshop will introduce the principles of sequence analysis and its relationship to protein structure and function. It will highlight common methods and tools for protein ...
The post-genomic era of biological network alignment | EURASIP Journal on Bioinformatics and Systems Biology | Full TextThe post-genomic era of biological network alignment | EURASIP Journal on Bioinformatics and Systems Biology | Full Text
Biological network alignment aims to find regions of topological and functional (dis)similarities between molecular networks of different species. Then, network alignment can guide the transfer of biological knowledge from well-studied model species to less well-studied species between conserved (aligned) network regions, thus complementing valuable insights that have already been provided by genomic sequence alignment. Here, we review computational challenges behind the network alignment problem, existing approaches for solving the problem, ways of evaluating their alignment quality, and the approaches biomedical applications. We discuss recent innovative efforts of improving the existing view of network alignment. We conclude with open research questions in comparative biological network research that could further our understanding of principles of life, evolution, disease, and therapeutics.
sequence alignment algorithmssequence alignment algorithms
Hi, Im new to programming so forgive me if I say something obviously stupid. Im interested in writing a program to do some primer-design tasks, among other things. The first thing I want the program to do, however, is a multiple sequence alignment. I realise this is like reinventing the wheel, which Id rather not do. Are there a few standard algorithms out there for this task? What about other standard molecualr biology algorithms? Also, maybe someone could suggest a few good beginning references for this sort of programing. Thanks! -- Susan http://www4.ncsu.edu/unity/users/s/sjhogart/public/home.html Check this! http://homepage.cistron.nl/~peterh/gsresources/ ...
Bioinformatics | Eastern Africa Statistical Training CentreBioinformatics | Eastern Africa Statistical Training Centre
Tools for Bioinformatics: DNA Sequence Analysis - Features of DNA sequence analysis, Approaches to EST analysis; Pairwise alignment techniques: Comparing two sequences, PAM and BLOSUM, Global alignment (The Needleman and Wunsch algorithm), Local Alignment (The Smith-Waterman algorithm), Dynamic programming, Pairwise database searching: Sequence analysis- BLAST and other related tools, Different methods of Multiple sequence alignment, Searching databases with multiple alignments; Alignment Scores, Design and Analysis of microarray experiments. ...
SAdLSA<...SAdLSA<...
From evolutionary interference, function annotation to structural prediction, protein sequence comparison has provided crucial biological insights. While many sequence alignment algorithms have been developed, existing approaches are often incapable of detecting hidden structural relationships in the "twilight zone" of low sequence identity. To address this critical problem, we introduce a computational algorithm that performs protein Sequence Alignments from deep-Learning of Structural Alignments (SAdLSA, silent "d"). The key idea is to implicitly learn the protein folding code from many thousands of structural alignments. We demonstrate that our models trained on Α-helical domains can be successfully transferred to recognize sequences encoding Β-sheet domains. Training and benchmarking on a larger, highly challenging data sets shows significant improvement over established approaches.. Notice: This server is freely available to all academic and non-commercial users ...
Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence AlignmentLearning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment
Regina Barzilay of MIT and Lillian Lee of Cornell University have developed a computer program that can automatically paraphrase English sentences: The program culls text from online news services on particular topics, determines distinguishing sentence patterns in these clusters, and employs these patterns to generate new sentences that convey the same message with different wording. Potential applications for such a tool include report summarization, document checking for repetition or plagiarism, and a way for authors to automatically rewrite their prose to readers of different backgrounds, which Lee describes as a style dial. Kevin Knight of the University of Southern California remarks that the program may even be able to help facilitate machine translation. Barzilay and Lee tested the program by having a computer categorize Agence France-Presse and Reuters articles according to subject, and then look for sentence clusters possessing similar words and phrases; the researchers used a ...
Edwards Lab: 2004Edwards Lab: 2004
BACKGROUND: The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments.. RESULTS: Here we present a new algorithm, GASP (Gapped Ancestral Sequence Prediction), for predicting ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments. Alignments may be of any size and contain gaps. GASP first assigns the positions of gaps in the phylogeny before using a likelihood-based approach centred on amino acid substitution matrices to assign ancestral amino acids. Important outgroup information is used by first working down from the tips of the tree to the root, using ...
BiBiServ2 - DialignBiBiServ2 - Dialign
DIALIGN is a software program for multiple sequence alignment developed by Burkhard Morgensternet al.. While standard alignment methods rely on comparing single residues and imposing gap penalties, DIALIGN constructs pairwise and multiple alignments by comparing entire segments of the sequences. No gap penalty is used. This approach can be used for both global and local alignment, but it is particularly successful in situations where sequences share only local homologies.. The latest version of the program, DIALIGN-TX, is described in Subramanian et al. (2008), Algorithms Mol. Biol. 3:6. A web server for this program is available at Goettingen Bioinformatics Compute Server (GOBICS). A web server for multiple alignment with user-defined constraints (anchor points) as described by Morgenstern et al. (2006), Algorithms Mol. Biol. 1:6 is also available through GOBICS.. During the last few years, DIALIGN has been successfully used by many researchers to align genomic sequences; some break-through ...
BiBiServ2 - DialignBiBiServ2 - Dialign
DIALIGN is a software program for multiple sequence alignment developed by Burkhard Morgensternet al.. While standard alignment methods rely on comparing single residues and imposing gap penalties, DIALIGN constructs pairwise and multiple alignments by comparing entire segments of the sequences. No gap penalty is used. This approach can be used for both global and local alignment, but it is particularly successful in situations where sequences share only local homologies.. The latest version of the program, DIALIGN-TX, is described in Subramanian et al. (2008), Algorithms Mol. Biol. 3:6. A web server for this program is available at Goettingen Bioinformatics Compute Server (GOBICS). A web server for multiple alignment with user-defined constraints (anchor points) as described by Morgenstern et al. (2006), Algorithms Mol. Biol. 1:6 is also available through GOBICS.. During the last few years, DIALIGN has been successfully used by many researchers to align genomic sequences; some break-through ...
Content providers - TeSS (Training eSupport System)Content providers - TeSS (Training eSupport System)
Jalview http://www.jalview.org/ https://tess.elixir-europe.org/content_providers/jalview Jalview (www.jalview.org) is free-to-use sequence alignment and analysis visualisation software that links genomic variants, protein alignments and 3D structure. Protein, RNA and DNA data can be directly accessed from public databases (e.g. Pfam, Rfam, PDB, UniProt and ENA etc.). Jalview has editing and annotation functionality within a fully integrated, multiple window interface. The sequence alignment programs Clustal Omega, Muscle, MAFFT, ProbCons, T-COFFEE, ClustalW, MSA Prob and GLProb can be run directly from within Jalview. Jalview integrates protein secondary structure prediction (JPred), generate trees, assesses consensus and conservation across sequence families. Journal quality figures can be generated from the results. The Jalview Desktop will run on Mac, MS Windows, Linux and any other platform that supports Java. It has been developed in Geoff Bartons group (www.compbio.dundee.ac.uk) in the ...
Content providers - TeSS (Training eSupport System)Content providers - TeSS (Training eSupport System)
Jalview http://www.jalview.org/ https://tess.elixir-europe.org/content_providers/jalview Jalview (www.jalview.org) is free-to-use sequence alignment and analysis visualisation software that links genomic variants, protein alignments and 3D structure. Protein, RNA and DNA data can be directly accessed from public databases (e.g. Pfam, Rfam, PDB, UniProt and ENA etc.). Jalview has editing and annotation functionality within a fully integrated, multiple window interface. The sequence alignment programs Clustal Omega, Muscle, MAFFT, ProbCons, T-COFFEE, ClustalW, MSA Prob and GLProb can be run directly from within Jalview. Jalview integrates protein secondary structure prediction (JPred), generate trees, assesses consensus and conservation across sequence families. Journal quality figures can be generated from the results. The Jalview Desktop will run on Mac, MS Windows, Linux and any other platform that supports Java. It has been developed in Geoff Bartons group (www.compbio.dundee.ac.uk) in the ...
Rice pseudomolecule-anchored cross-species DNA sequence alignments indicate regional genomic variation in expressed sequence...Rice pseudomolecule-anchored cross-species DNA sequence alignments indicate regional genomic variation in expressed sequence...
Various methods have been developed to explore inter-genomic relationships among plant species. Here, we present a sequence similarity analysis based upon comparison of transcript-assembly and methylation-filtered databases from five plant species and physically anchored rice coding sequences. A comparison of the frequency of sequence alignments, determined by MegaBLAST, between rice coding sequences in TIGR pseudomolecules and annotations vs 4.0 and comprehensive transcript-assembly and methylation-filtered databases from Lolium perenne (ryegrass), Zea mays (maize), Hordeum vulgare (barley), Glycine max (soybean) and Arabidopsis thaliana (thale cress) was undertaken. Each rice pseudomolecule was divided into 10 segments, each containing 10% of the functionally annotated, expressed genes. This indicated a correlation between relative segment position in the rice genome and numbers of alignments with all the queried monocot and dicot plant databases. Colour-coded moving windows of 100 functionally
MUSCLE: multiple sequence alignment with high accuracy and high throughputMUSCLE: multiple sequence alignment with high accuracy and high throughput
We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent …
Multiple sequence Alignment tool - Bioinformatics and BiostatisticsMultiple sequence Alignment tool - Bioinformatics and Biostatistics
Another possibility is to use bioedit that is a alignemnt sequence editor software. this allows easily to align by Clustal the selected sequences and also is possible to performs blast searches directly rom the main windows, retrieve sequences (with all the GenBank information) directli from NCBI and align again... if well setted is also possible to use the complete phylip package to make trees ...
Revision of the Nomenclature for the Bacillus thuringiensis Pesticidal Crystal Proteins | Microbiology and Molecular Biology...Revision of the Nomenclature for the Bacillus thuringiensis Pesticidal Crystal Proteins | Microbiology and Molecular Biology...
Fig. 1. Phylogram demonstrating amino acid sequence identity among Cry and Cyt proteins. This phylogenetic tree is modified from a TREEVIEW visualization of NEIGHBOR treatment of a CLUSTAL W multiple alignment and distance matrix of the full-length toxin sequences, as described in the text. The gray vertical bars demarcate the four levels of nomenclature ranks. Based on the low percentage of identical residues and the absence of any conserved sequence blocks in multiple-sequence alignments, the lower four lineages are not treated as part of the main toxin family, and their nodes have been replaced with dashed horizontal lines in this figure. ...
Matrix and Gap CostsMatrix and Gap Costs
A key element in evaluating the quality of a pairwise sequence alignment is the "substitution matrix", which assigns a score for aligning any possible pair of residues. The theory of amino acid substitution matrices is described in [1], and applied to DNA sequence comparison in [2]. In general, different substitution matrices are tailored to detecting similarities among sequences that are diverged by differing degrees [1-3]. A single matrix may nevertheless be reasonably efficient over a relatively broad range of evolutionary change [1-3]. Experimentation has shown that the BLOSUM-62 matrix [4] is among the best for detecting most weak protein similarities. For particularly long and weak alignments, the BLOSUM-45 matrix may prove superior. A detailed statistical theory for gapped alignments has not been developed, and the best gap costs to use with a given substitution matrix are determined empirically. Short alignments need to be relatively strong (i.e. have a higher percentage of matching ...
Seq2Logo: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence...Seq2Logo: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence...
TY - JOUR. T1 - Seq2Logo: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence weighting, pseudo counts and two-sided representation of amino acid enrichment and depletion. AU - Thomsen, Martin Christen Frølund. AU - Nielsen, Morten. PY - 2012. Y1 - 2012. N2 - Seq2Logo is a web-based sequence logo generator. Sequence logos are a graphical representation of the information content stored in a multiple sequence alignment (MSA) and provide a compact and highly intuitive representation of the position-specific amino acid composition of binding motifs, active sites, etc. in biological sequences. Accurate generation of sequence logos is often compromised by sequence redundancy and low number of observations. Moreover, most methods available for sequence logo generation focus on displaying the position-specific enrichment of amino acids, discarding the equally valuable information related to amino acid depletion. Seq2logo aims at resolving ...
Multiz Alignments of 100 VertebratesMultiz Alignments of 100 Vertebrates
This track shows multiple alignments of 100 vertebrate species and measurements of evolutionary conservation using two methods (phastCons and phyloP) from the PHAST package, for all species. The multiple alignments were generated using multiz and other tools in the UCSC/Penn State Bioinformatics comparative genomics alignment pipeline. Conserved elements identified by phastCons are also displayed in this track. PHAST/Multiz are built from chains ("alignable") and nets ("syntenic"), see the documentation of the Chain/Net tracks for a description of the complete alignment process. PhastCons is a hidden Markov model-based method that estimates the probability that each nucleotide belongs to a conserved element, based on the multiple alignment. It considers not just each individual alignment column, but also its flanking columns. By contrast, phyloP separately measures conservation at individual columns, ignoring the effects of their neighbors. As a consequence, the phyloP plots have a less smooth ...
Myoskeletal Alignment Techniques Overview - Erik DaltonMyoskeletal Alignment Techniques Overview - Erik Dalton
Myoskeletal Alignment Techniques is a term first coined by Dalton in the early 1980s. However, Dalton never stops developing the MAT system. Over the years, the work of Phillip Greenman, Serge Gracovetsky and many other visionaries in kinesiology and human performance have been integrated into his training programs. By teaching how to identify and correct dysfunctional, neurologically-driven strain patterns before they become pain patterns, he has created one of the most integrative and complete perspectives on pain management.. MAT practitioners learn how to take clients through a series of sessions in deep tissue therapy that calms hyper-excited nerve receptors. When the pain-generating stimulus is effectively interrupted, new memories can be programmed into muscle cells by inhibiting the chemical activation of pain, which allows the brain to downgrade its signals for chronic protective spasms.. Of course, effective bodywork depends on much more than intellectual knowledge. Daltons program ...
Probabilistic sequence alignments: realistic models with efficient algorithms | Research - Institut PasteurProbabilistic sequence alignments: realistic models with efficient algorithms | Research - Institut Pasteur
Link to Pubmed [PMID] - 17359063. Phys. Rev. Lett. 2007 Feb;98(7):078101. Alignment algorithms usually rely on simplified models of gaps for computational efficiency. Based on correspondences between alignments and structural models for nucleic acids, and using methods from statistical mechanics, we show that alignments with realistic laws for gaps can be computed with fast algorithms. Improved performances of probabilistic alignments with realistic models of gaps are illustrated. By contrast with optimization-based alignments, such improvements with realistic laws are not observed. General perspectives for biological and physical modelings are mentioned.. https://www.ncbi.nlm.nih.gov/pubmed/17359063 ...
ArchAlign: Coordinate-free chromatin alignment reveals novel architectures<...ArchAlign: Coordinate-free chromatin alignment reveals novel architectures<...
TY - JOUR. T1 - ArchAlign. T2 - Coordinate-free chromatin alignment reveals novel architectures. AU - Lai, William K.M.. AU - Buck, Michael J.. PY - 2010/12/23. Y1 - 2010/12/23. N2 - To facilitate identification and characterization of genomic functional elements, we have developed a chromatin architecture alignment algorithm (ArchAlign). ArchAlign identifies shared chromatin structural patterns from high-resolution chromatin structural datasets derived from next-generation sequencing or tiled microarray approaches for user defined regions of interest. We validated ArchAlign using well characterized functional elements, and used it to explore the chromatin structural architecture at CTCF binding sites in the human genome. ArchAlign is freely available at http://www.acsu.buffalo.edu/~mjbuck/ArchAlign.html.. AB - To facilitate identification and characterization of genomic functional elements, we have developed a chromatin architecture alignment algorithm (ArchAlign). ArchAlign identifies shared ...
SAMMate: a GUI tool for processing short read alignments in SAM/BAM format | MetaSAMMate: a GUI tool for processing short read alignments in SAM/BAM format | Meta
Next Generation Sequencing (NGS) technology generates tens of millions of short reads for each DNA/RNA sample. A key step in NGS data analysis is the short read alignment of the generated sequences to a reference genome. Although storing alignment information in the Sequence Alignment/M...read more ...
Enhancing the scalability of consistency-based progressive multiple sequences alignment applications - TechTalks.tvEnhancing the scalability of consistency-based progressive multiple sequences alignment applications - TechTalks.tv
TechTalks.tv is making it super-easy to publish, search and learn from slide-based videos, all in order to share educational content on the web.
Prediction of Functional Sites by Analysis of Sequence and Structure Conservation | Bioinformatics and Genomics @ CRGPrediction of Functional Sites by Analysis of Sequence and Structure Conservation | Bioinformatics and Genomics @ CRG
We present a method for prediction of functional sites in a set of aligned protein sequences. The method selects sites which are both well conserved and clustered together in space, as inferred from the 3D structures of proteins included in the alignment. We tested the method using 86 alignments from the NCBI CDD database, where the sites of experimentally determined ligand and/or macromolecular interactions are annotated. In agreement with earlier investigations, we found that functional site predictions are most successful when overall background sequence conservation is low, such that sites under evolutionary constraint become apparent. In addition, we found that averaging of conservation values across spatially clustered sites improves predictions under certain conditions: that is, when overall conservation is relatively high and when the site in question involves a large macromolecular binding interface. Under these conditions it is better to look for clusters of conserved sites than to ...
AlignmentAlgorithms: Collection of alignment algorithmsAlignmentAlgorithms: Collection of alignment algorithms
generalized Algebraic Dynamic Programming. A selection of (sequence) alignment algorithms. Both terminal, and syntactic variables, as well as the index type is not fixed here. This makes it possible to select the correct structure of the grammar here, but bind the required data type for alignment in user code.. That being said, these algorithms are mostly aimed towards sequence alignment problems.. List of grammars for sequences:. ...
Difference between revisions of PyNAST - Free Software DirectoryDifference between revisions of "PyNAST" - Free Software Directory
alignment of short DNA sequences The package provices a reimplementation of the Nearest Alignment Space Termination tool in Python. It was prepared for next generation sequencers. Given a set of sequences and a template alignment, PyNAST will align the input sequences against the template alignment, and return a multiple sequence alignment which contains the same number of positions (or columns) as the template alignment. This facilitates the analysis of new sequences in the context of existing alignments, and additional data derived from existing alignments such as phylogenetic trees. Because any protein or nucleic acid sequences and template alignments can be provided, PyNAST is not limited to the analysis of 16s rDNA sequences. ...
BiO BB] time efficient global alignment algorithmBiO BB] time efficient global alignment algorithm
2009/8/4 Ryan Golhar ,golharam at umdnj.edu,: ,,, Im trying to perform a large amount of sequence alignments of long DNA ,,, sequences, some up to 163,000+ bp in length. I was trying to use the ,,, standard Needleman-Wunsch algorithm, but the matrix used requires a ,,, large amount of memory...about 100 GB of memory. This obviously wont ,,, work. ,, ,, How many were you trying to align? You mean 163kb or 163Mb? ,, I was looking for test or comparisons for some alignment code I had which ,, indexed the target sequences, dont recall the suggestions ,, for that discussion but I was able to do simple genomes reasonably well ( ,, I think I used 2 strains of e coli or something about 5 megs long) ,, on a desktop. If you can find responses to my request from a few years ago ,, that may ( or may not ) help. Id offer my code, and indeed I think ,, I have it on a website, but I stopped development and not sure ,, it is nearly useful as-is unless you just want coarse alignment on ,, two similar ...
Phylo DNA PuzzlePhylo DNA Puzzle
Traditionally, multiple sequence alignment algorithms use computationally complex heuristics to align the sequences. Unfortunately, the use of heuristics do not guarantee global optimization as it would be prohibitively computationally expensive to achieve an optimal alignment. This is due in part to the sheer size of the genome, which consists of roughly three billion base pairs, and the increasing computational complexity resulting from each additional sequence in an alignment.. ...
BLAST - OpenWetWareBLAST - OpenWetWare
Basic Local Alignment Search Tool, or BLAST, is an algorithm for comparing biological sequences, such as the amino-acid sequences of different proteins or the DNA sequences. A BLAST search enables a researcher to compare a query sequence with a library or database of sequences, and identify library sequences that resemble the query sequence above a certain threshold. For example, following the discovery of a previously unknown gene in the mouse, a scientist will typically perform a BLAST search of the human genome to see if human beings carry a similar gene; BLAST will identify sequences in the human genome that resemble the mouse gene based on similarity of sequence. BLAST is one of the most widely used bioinformatics programs, probably because it addresses a fundamental problem and the algorithm emphasizes speed over sensitivity. This emphasis on speed is vital to making the algorithm practical on the huge genome databases currently available, although subsequent algorithms can be even faster. ...
Improving protein structure similarity searches using domain boundaries based on conserved sequence information | BMC...Improving protein structure similarity searches using domain boundaries based on conserved sequence information | BMC...
As the amount of diverse biological data continues to grow, it is important for new methods of analysis to be devised and current methods to be improved. The ability to detect that two proteins have diverged from a common ancestor allows one to infer functional similarity between the two. A common method for identifying similarity between proteins is the use of sequence alignment tools such as FASTA [1] and BLAST [2], which provide an alignment of two sequences and a score indicating whether the alignment is significant or could be attributed to chance. The comparison of protein structures allows one to peer back farther into evolutionary time, based on the concept that a form or structure remains similar long after sequence similarity has become undetectable [3-6]. There are many methods [7-15] and databases [16-19] currently available for protein structure comparisons. While the performance of the methods and databases available are for the most part satisfactory, it is not unusual for such ...
science software (mol biol/biochem/biology) under Linuxscience software (mol biol/biochem/biology) under Linux
On 04 Oct 1996 16:41:22 -0600, zinc ,zinc at zifi.genetics.utah.edu, wrote: ,im attempting to compile a list of software that either people have ,claimed runs under Linux or that is known to run under Linux for the ,people at Caldera (Caldera is Ray Noordas ( of Novell fame ) new ,company). There are several others .... SignalScal - scan for transcription factor binding sites - version 4.07, written in C, compiles fine - ftp://biosci.umn.edu/pub/sigscan/unix PIMA - pattern induced multiple sequence alignment - version 1.40, written in C, compiles fine - ftp://gc.bcm.tmc.edu/pub/software/pima Predator - structural prediction based on multiple alignments - version 1.0, written in C, compiles fine - ftp://ftp.ebi.ac.uk/pub/software/unix/predator ClustalW - pairwise and multiple alignments - version 1.60, written in C, compiles fine - ftp://ftp.ebi.ac.uk/pub/software/unix Seqsee - protein sequence analysis package - version 1.2, written in C, compiles fine - available upon request from seqsee at ...
Smith-Waterman algorithm BioCode | BioCodeKB - Learn BioinformaticsSmith-Waterman algorithm BioCode | BioCodeKB - Learn Bioinformatics
Learn Bioinformatics Online Smith Waterman algorithm was first proposed by Temple F. Smith and Michael S. Waterman in 1981. The algorithm explains the local sequence alignment, ....
Identity and similarity for Multiple Sequence Alignment (MSA) of proteins - Biology Stack ExchangeIdentity and similarity for Multiple Sequence Alignment (MSA) of proteins - Biology Stack Exchange
begingroup$ Thanks you for the reply. I just finished reading the documentation. I found out that I can use Chimera to see the percentage of identity, so one problem is solved. The main problem is of a different nature: lets say that I have the MSA from residue 1 to 100 of the query. I would like to have a tool that automatically computes the number of insertions, deletions etc... Some numerical quantities that I can use to see if the alignment is good and how much. Thank you. $\endgroup$ - wrong_path Dec 21 16 at 16:59 ...
Needleman-Wunsch algorithmNeedleman-Wunsch algorithm
Smith-Waterman algorithmSmith-Waterman algorithm
Austronesian peoplesAustronesian peoples
Dynamic programmingDynamic programming
SH3D21SH3D21
Dot plot (bioinformatics)Dot plot (bioinformatics)
Point accepted mutationPoint accepted mutation
Altaic languagesAltaic languages
CASPCASP
Inferring horizontal gene transferInferring horizontal gene transfer
C10orf76C10orf76
ClustalClustal
HH-suiteHH-suite
BAli-PhyBAli-Phy
PANDIT (database)PANDIT (database)
TMEM229BTMEM229B
DECIPHER (software)DECIPHER (software)
Ewan BirneyEwan Birney
MAFFTMAFFT
Align-mAlign-m
Richard M. DurbinRichard M. Durbin
2D gel analysis software2D gel analysis software
Lorraine LisieckiLorraine Lisiecki
Circular permutation in proteinsCircular permutation in proteins
Bacterial phylodynamicsBacterial phylodynamics
LRRN3LRRN3
Molecular phylogeneticsMolecular phylogenetics
Zipfs lawZipf's law
TunicateTunicate
Similarity measureSimilarity measure
Quantitative trait locusQuantitative trait locus
Clave (rhythm)Clave (rhythm)
LeafLeaf
OctopusOctopus
GenBankGenBank
Neo-Piagetian theories of cognitive developmentNeo-Piagetian theories of cognitive development
EndiannessEndianness
Bioinformática, a enciclopedia libreBioinformática, a enciclopedia libre
Nuclear magnetic resonance spectroscopy of nucleic acidsNuclear magnetic resonance spectroscopy of nucleic acids
Dom languageDom language
ChicannáChicanná
Reciprocating engineReciprocating engine
Category:Bioinformatics softwareCategory:Bioinformatics software
International Commission on StratigraphyInternational Commission on Stratigraphy
Non-invasive intracranial pressure measurement methodsNon-invasive intracranial pressure measurement methods
Aminoacyl tRNA synthetaseAminoacyl tRNA synthetase
ProteinProtein
HemoglobinHemoglobin
HerbalismHerbalism
DenisovanDenisovan
Gene ontologyGene ontology
Women in Military Service for America MemorialWomen in Military Service for America Memorial
InfectionInfection
Computational biologyComputational biology
Česlovas Venclovas - VikipedijaČeslovas Venclovas - Vikipedija
AnatomyOrganismsDiseasesChemicals and DrugsAnalytical, Diagnostic and Therapeutic Techniques and EquipmentPsychiatry and PsychologyPhenomena and ProcessesDisciplines and OccupationsAnthropology, Education, Sociology and Social PhenomenaTechnology, Industry, AgricultureInformation ScienceHealth Care
Sequence AlignmentSequence Analysis, ProteinSoftwareAlgorithmsMolecular Sequence DataAmino Acid SequenceComputational BiologyPhylogenySequence Homology, Amino AcidProteinsDatabases, ProteinSequence Analysis, DNAModels, MolecularConserved SequenceInternetBase SequenceEvolution, MolecularUser-Computer InterfaceSoftware ValidationStructural Homology, ProteinSequence AnalysisSequence Analysis, RNAProtein Structure, TertiaryComputing MethodologiesSequence HomologyComputer GraphicsProtein Structure, SecondaryMarkov ChainsProtein ConformationGenomicsComputer SimulationDatabases, GeneticSequence Homology, Nucleic AcidGenomeBinding SitesDatabases, FactualWord ProcessingDatabases, Nucleic AcidModels, GeneticModels, StatisticalInformation Storage and RetrievalPattern Recognition, AutomatedCloning, MolecularAmino Acid MotifsConsensus SequenceLikelihood FunctionsReproducibility of ResultsSoftware DesignMutagenesis, Site-DirectedINDEL MutationProgramming LanguagesCluster AnalysisRNAEscherichia coliProtein FoldingDatabase Management SystemsBacterial ProteinsNucleic Acid ConformationBone MalalignmentMultigene FamilyModels, ChemicalMutationArtificial IntelligenceAmino Acid SubstitutionSpecies SpecificityCatalytic DomainDNAProtein BindingStructure-Activity RelationshipSubstrate SpecificityCrystallography, X-RaySensitivity and SpecificityGenetic VariationExpressed Sequence TagsWork SimplificationBayes TheoremCatalysisRecombinant ProteinsProbabilityDNA, ComplementaryRNA, UntranslatedOpen Reading FramesEntropyArchaeaSarcocystidaeDNA PrimersBase PairingComputersGenome, HumanBenchmarkingData CompressionQuality ControlChromosome MappingMonte Carlo MethodGenome, BacterialGenome, ViralData Interpretation, StatisticalComputer Communication NetworksPan troglodytesTetraodontiformesKineticsPolymerase Chain ReactionRNA, RibosomalGenes, OverlappingEnzyme StabilityNucleotide MotifsAmino AcidsPlant ProteinsExonsBiological EvolutionGene Expression ProfilingProtein EngineeringHypermediaMolecular Sequence AnnotationCodonProtein Structure, QuaternaryDNA, IntergenicHigh-Throughput Nucleotide SequencingDNA, BacterialGenes, BacterialBacteriaGene LibraryKnee JointMathematical ComputingAutomationGenome, PlantSystems IntegrationCircular DichroismNeural Networks (Computer)Membrane ProteinsHydrogen BondingIntronsEvaluation Studies as TopicEscherichia coli ProteinsHMG-Box DomainsCattleEukaryotic CellsRecombination, GeneticDNA Mutational AnalysisOryza sativaRNA, BacterialMammalsNucleotidesDNA Barcoding, TaxonomicSaccharomyces cerevisiaeViral ProteinsSolanaceaePeptidesSyntenySequence DeletionModels, TheoreticalDocumentationMutagenesisNational Library of Medicine (U.S.)Mutagenesis, InsertionalHistidineDNA, RibosomalLigandsArchaeal ProteinsCarrier ProteinsImaging, Three-DimensionalMolecular ConformationProkaryotic CellsPseudogenesDNA, ChloroplastDimerizationSurgery, Computer-AssistedEnzymesModels, BiologicalClassificationTranscription FactorsRNA, Ribosomal, 16SRepetitive Sequences, Nucleic AcidStatic ElectricityModels, StructuralProtein Interaction MappingThermodynamicsPeptide FragmentsPlantsTibiaCysteineMethanococcusBase CompositionMolecular StructureRNA, MessengerTime Factors
Sequence alignment - WikipediaSequence alignment - Wikipedia
Multiple sequence alignment - WikipediaMultiple sequence alignment - Wikipedia
Incremental Multiple Sequence Alignment | SpringerLinkIncremental Multiple Sequence Alignment | SpringerLink
MSAProbs: Multiple Sequence Alignment download | SourceForge.netMSAProbs: Multiple Sequence Alignment download | SourceForge.net
DbClustal | Multiple Sequence Alignment | EMBL-EBIDbClustal | Multiple Sequence Alignment | EMBL-EBI
Burrows-Wheeler DNA Sequence Alignment-Removing Load ImbalanceBurrows-Wheeler DNA Sequence Alignment-Removing Load Imbalance
multiple sequence alignmentmultiple sequence alignment
sequence alignment algorithmssequence alignment algorithms
Non-approximability of Weighted Multiple Sequence Alignment | SpringerLinkNon-approximability of Weighted Multiple Sequence Alignment | SpringerLink
Multiple sequence alignment with Clustal X. - PubMed - NCBIMultiple sequence alignment with Clustal X. - PubMed - NCBI
Hardware Accelerated Sequence Alignment with TracebackHardware Accelerated Sequence Alignment with Traceback
Converting sequence alignment formatsConverting sequence alignment formats
Support for linguistic macrofamilies from weighted sequence alignment | PNASSupport for linguistic macrofamilies from weighted sequence alignment | PNAS
The Sequence Alignment/Map format and SAMtools. - PubMed - NCBIThe Sequence Alignment/Map format and SAMtools. - PubMed - NCBI
Bioclusters] Parallel Sequence Alignment toolBioclusters] Parallel Sequence Alignment tool
Sequence alignment package for LaTeX?Sequence alignment package for LaTeX?
Essential Concepts - Sequence Alignment | CourseraEssential Concepts - Sequence Alignment | Coursera
Sequence alignment - WikipediaSequence alignment - Wikipedia
Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence AlignmentLearning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment
Sequence alignment (howto) - Bioinformatics.Org WikiSequence alignment (howto) - Bioinformatics.Org Wiki
CiteSeerX - Muscle: multiple sequence alignment with high accuracy and high throughputCiteSeerX - Muscle: multiple sequence alignment with high accuracy and high throughput
Multiple Sequence Alignment Using a Genetic Algorithm and GLOCSAMultiple Sequence Alignment Using a Genetic Algorithm and GLOCSA
Sequence Alignment & Analysis: New in Mathematica 7Sequence Alignment & Analysis: New in Mathematica 7
The Sequence Alignment/Map format and SAMtoolsThe Sequence Alignment/Map format and SAMtools
MUSCLE: multiple sequence alignment with high accuracy and high throughputMUSCLE: multiple sequence alignment with high accuracy and high throughput
CiteSeerX - Multiple sequence alignment with the Clustal series of programsCiteSeerX - Multiple sequence alignment with the Clustal series of programs
Debian -- File list of package alter-sequence-alignment/stretch/mips64elDebian -- File list of package alter-sequence-alignment/stretch/mips64el
Alignment & Sequence Variation 4: Bowtie - Week Three | CourseraAlignment & Sequence Variation 4: Bowtie - Week Three | Coursera
lopez-et-al 2010 | Phylogenetic Tree | Sequence Alignmentlopez-et-al 2010 | Phylogenetic Tree | Sequence Alignment
ISA: Inferred from Sequence Alignment | Gene Ontology ConsortiumISA: Inferred from Sequence Alignment | Gene Ontology Consortium
AnatomyOrganismsDiseasesChemicals and DrugsAnalytical, Diagnostic and Therapeutic Techniques and EquipmentPsychiatry and PsychologyPhenomena and ProcessesDisciplines and OccupationsAnthropology, Education, Sociology and Social PhenomenaTechnology, Industry, AgricultureInformation ScienceHealth Care
Sequence AlignmentSequence Analysis, ProteinSoftwareAlgorithmsMolecular Sequence DataAmino Acid SequenceComputational BiologyPhylogenySequence Homology, Amino AcidProteinsDatabases, ProteinSequence Analysis, DNAModels, MolecularConserved SequenceInternetBase SequenceEvolution, MolecularUser-Computer InterfaceSoftware ValidationStructural Homology, ProteinSequence AnalysisSequence Analysis, RNAProtein Structure, TertiaryComputing MethodologiesSequence HomologyComputer GraphicsProtein Structure, SecondaryMarkov ChainsProtein ConformationGenomicsComputer SimulationDatabases, GeneticSequence Homology, Nucleic AcidGenomeBinding SitesDatabases, FactualWord ProcessingDatabases, Nucleic AcidModels, GeneticModels, StatisticalInformation Storage and RetrievalPattern Recognition, AutomatedCloning, MolecularAmino Acid MotifsConsensus SequenceLikelihood FunctionsReproducibility of ResultsSoftware DesignMutagenesis, Site-DirectedINDEL MutationProgramming LanguagesCluster AnalysisRNAEscherichia coliProtein FoldingDatabase Management SystemsBacterial ProteinsNucleic Acid ConformationBone MalalignmentMultigene FamilyModels, ChemicalMutationArtificial IntelligenceAmino Acid SubstitutionSpecies SpecificityCatalytic DomainDNAProtein BindingStructure-Activity RelationshipSubstrate SpecificityCrystallography, X-RaySensitivity and SpecificityGenetic VariationExpressed Sequence TagsWork SimplificationBayes TheoremCatalysisRecombinant ProteinsProbabilityDNA, ComplementaryRNA, UntranslatedOpen Reading FramesEntropyArchaeaSarcocystidaeDNA PrimersBase PairingComputersGenome, HumanBenchmarkingData CompressionQuality ControlChromosome MappingMonte Carlo MethodGenome, BacterialGenome, ViralData Interpretation, StatisticalComputer Communication NetworksPan troglodytesTetraodontiformesKineticsPolymerase Chain ReactionRNA, RibosomalGenes, OverlappingEnzyme StabilityNucleotide MotifsAmino AcidsPlant ProteinsExonsBiological EvolutionGene Expression ProfilingProtein EngineeringHypermediaMolecular Sequence AnnotationCodonProtein Structure, QuaternaryDNA, IntergenicHigh-Throughput Nucleotide SequencingDNA, BacterialGenes, BacterialBacteriaGene LibraryKnee JointMathematical ComputingAutomationGenome, PlantSystems IntegrationCircular DichroismNeural Networks (Computer)Membrane ProteinsHydrogen BondingIntronsEvaluation Studies as TopicEscherichia coli ProteinsHMG-Box DomainsCattleEukaryotic CellsRecombination, GeneticDNA Mutational AnalysisOryza sativaRNA, BacterialMammalsNucleotidesDNA Barcoding, TaxonomicSaccharomyces cerevisiaeViral ProteinsSolanaceaePeptidesSyntenySequence DeletionModels, TheoreticalDocumentationMutagenesisNational Library of Medicine (U.S.)Mutagenesis, InsertionalHistidineDNA, RibosomalLigandsArchaeal ProteinsCarrier ProteinsImaging, Three-DimensionalMolecular ConformationProkaryotic CellsPseudogenesDNA, ChloroplastDimerizationSurgery, Computer-AssistedEnzymesModels, BiologicalClassificationTranscription FactorsRNA, Ribosomal, 16SRepetitive Sequences, Nucleic AcidStatic ElectricityModels, StructuralProtein Interaction MappingThermodynamicsPeptide FragmentsPlantsTibiaCysteineMethanococcusBase CompositionMolecular StructureRNA, MessengerTime Factors
AlgorithmBioinformaticsAlgorithmsAbstractEvolutionaryProteinsSimilar sequencesNucleicResiduesPfamQuality of sequence alignmentsClustalHomologyProgressive alignmentPairwise alignmentLocal alignmentReference alignmentsBLASTBetter alignmentsDifferent alignmentsRegions of similarityStructuresApproachesQuery sequencesBiologicalGapsComputational biologyInferInput sequencesPairsFASTAStructuralAlignerGenomesAnalysesOrganismGenomic dataGlobal alignmentPhylogenetic TreeAccurateNucleotide sequenceReadsRedundancyNewly sequencedHomologousProtein multipleProducesPair of sequencesWidelyResidueMethodsAnalysisMultiple protein
Algorithm32
Bioinformatics12
Algorithms15
Abstract3
  • We take profit from some results on Grammatical Inference that allow us to build iteratively an abstract machine that considers in each inference step an increasing amount of sequences. (springer.com)
  • Abstract The increased collection, storage, and analysis of person-specific DNA sequences poses serious challenges to the protection of the identities to which such sequences correspond. (scribd.com)
  • Abstract-While the multiple sequence alignment output by an aligner strongly depends on the parameter values used for the alignment scoring function (such as the choice of gap penalties and substitution scores), most users rely on the single default parameter setting provided by the aligner. (psu.edu)
Evolutionary19
Proteins13
Similar sequences5
Nucleic4
Residues9
Pfam3
  • Here, we have selected/clicked PF18225 and it opens go to http://pfam.xfam.org/family/PF18225 and shows complete details about it, including sequence alignments. (tutorialspoint.com)
  • We describe the derivation of a set of sub-type groupings derived from an automated parsing of alignments from PFAM and the SWISSPROT database, and use this to perform a large-scale assessment. (umd.edu)
  • Some domain resources, such as PFAM ( 1 ) and ProDom ( 2 ), rely on the automated methods of multiple sequence alignment while others, such as SMART ( 3 ) and CDD ( 4 ), employ careful manual intervention in constructing the domain models. (pubmedcentralcanada.ca)
Quality of sequence alignments1
Clustal7
Homology3
Progressive alignment5
Pairwise alignment3
Local alignment5
Reference alignments1
  • The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. (psu.edu)
BLAST13
Better alignments2
Different alignments2
Regions of similarity2
Structures8
Approaches7
Query sequences3
  • Calculating a global alignment is a form of global optimization that "forces" the alignment to span the entire length of all query sequences. (wikipedia.org)
  • Thus, the likelihood of finding close homologs for query sequences is smaller, and the alignments will in general have lower scores. (bibsys.no)
  • Here, we propose a method that addresses this problem by first aligning query sequences against a large database representing the corpus of known sequences, and then constructing indirect (or transitive) alignments by combining the results with alignments from the large database against the desired target database. (bibsys.no)
Biological5
Gaps11
Computational biology1
Infer4
  • The process of evaluating a sequence alignment involves checking that the length of the matching region and the percent identity with the matching sequence are sufficient to infer shared function. (geneontology.org)
  • Pairwise is easy to understand and exceptional to infer from the resulting sequence alignment. (tutorialspoint.com)
  • In addition, information from closely related sequences can be used to infer sites as "permanent" insertions that cannot be matched in subsequent alignments, so that distinct insertion events are correctly kept separate even when they occur at exactly the same position. (anthropology.net)
  • Traditional multiple sequence alignment methods disregard the phylogenetic implications of gap patterns that they create and infer systematically biased alignments with excess deletions and substitutions, too few insertions, and implausible insertion-deletion-event histories. (sciencemag.org)
Input sequences5
Pairs6
  • Our approach applies multiple-sequence alignment to sentences gathered from unannotated comparable corpora: it learns a set of paraphrasing patterns represented by word lattice pairs and automatically determines how to apply these patterns to rewrite new sentences. (cornell.edu)
  • The MSA program optimizes the sum of all of the pairs of characters at each position in the alignment (the so-called sum of pair score) and has been implemented in a software program for constructing multiple sequence alignments. (wikipedia.org)
  • The DNALA method chooses pairs of sequences to be anonymized to a sequence of minimal distance between the pair, and generalizes the pair accordingly. (scribd.com)
  • Scientists can now generate the rough equivalent of an entire human genome (~3 billion base-pairs of DNA) in just a few days with one single sequencing instrument. (umd.edu)
  • It shows that for protein pairs with low sequence similarity (less than 12% sequence identity) the new structural features alone or in conjunction with profile-based information lead to alignments that are considerably better than those obtained by previous schemes. (umn.edu)
  • Distinct processes are depicted with structure classes, the moves among the structure classes described as a Markov process, and the whole alignment process is described with a two-level Hidden Markov Model (HMM) outputting pairs of aligned characters. (royalsocietypublishing.org)
FASTA5
  • The initial guide tree is determined by an efficient clustering method such as neighbor-joining or UPGMA, and may use distances based on the number of identical two letter sub-sequences (as in FASTA rather than a dynamic programming alignment). (wikipedia.org)
  • So the format says that it's bowtie2-build followed by a number of options, which are obviously null, followed by the reference fasta sequence, and then the prefix for the index. (coursera.org)
  • 2. if ur taking from 'NCBI' what u have to do is select the sequence and click to display in FASTA format and ask to send the file to desktop. (protocol-online.org)
  • By this way u can save the entire sequence in fasta format as a single file which u can use further for alignment. (protocol-online.org)
  • The data may be either a list of database accession numbers, NCBI gi numbers, or sequences in FASTA format. (nih.gov)
Structural3
  • The absence of substitutions, or the presence of only very conservative substitutions (that is, the substitution of amino acids whose side chains have similar biochemical properties) in a particular region of the sequence, suggest that this region has structural or functional importance. (wikipedia.org)
  • This paper studies the impact on the alignment quality of a new class of predicted local structural features that measure how well fixed-length backbone fragments centered around each residue-pair align with each other. (umn.edu)
  • These results suggest that insertions and sequence turnover are more common than is currently thought and challenge the conventional picture of sequence evolution and mechanisms of functional and structural changes. (sciencemag.org)
Aligner5
  • Padding operations can be absent when an aligner does not support multiple sequence alignment. (nih.gov)
  • TextPAIR is a scalable and high-performance sequence aligner for humanities text analysis designed to identify "similar passages" in large collections of texts. (uchicago.edu)
  • A parameter advisor has two ingredients: (i) a set of parameter choices to select from, and (ii) an estimator that provides an estimate of the accuracy of the alignment computed by the aligner using a parameter choice. (psu.edu)
  • We identify bottlenecks that lead to processor underutilization and discuss the implications of our analysis on next-generation sequence aligner design. (eurecom.fr)
  • We present the Scalable Nucleotide Alignment Program (SNAP), a new short and long read aligner that is both more accurate (i.e., aligns more reads with fewer errors) and 10-100x faster than state-of-the-art tools such as BWA. (arxiv.org)
Genomes4
Analyses1
Organism2
Genomic data2
Global alignment3
Phylogenetic Tree2
Accurate5
Nucleotide sequence2
Reads12
Redundancy3
Newly sequenced1
  • Is there a way I can decisively check whether or not this gene exists in its entirety, or partially, in the contig set of the newly sequenced genome, and if yes, determine its location? (scientistsolutions.com)
Homologous3
Protein multiple2
Produces3
Pair of sequences1
Widely3
Residue4
Methods15
Analysis14
Multiple protein1
PLOS ONE: Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment
PLOS ONE: Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment (journals.plos.org)
Sequence alignment - Wikipedia
Sequence alignment - Wikipedia (en.wikipedia.org)
Multiple sequence alignment - Wikipedia
Multiple sequence alignment - Wikipedia (en.wikipedia.org)
Rethinking the Origin of Primates by Reconstructing Their Diel Activity Patterns Using Genetics and Morphology | Scientific...
Rethinking the Origin of Primates by Reconstructing Their Diel Activity Patterns Using Genetics and Morphology | Scientific... (nature.com)
Genetic characterization of cysteine-rich type-b avenin-like protein coding genes in common wheat | Scientific Reports
Genetic characterization of cysteine-rich type-b avenin-like protein coding genes in common wheat | Scientific Reports (nature.com)
Transcriptional repressor PRR5 directly regulates clock-output pathways | PNAS
Transcriptional repressor PRR5 directly regulates clock-output pathways | PNAS (pnas.org)
Structure of the plastic-degrading Ideonella sakaiensis MHETase bound to a substrate | Nature Communications
Structure of the plastic-degrading Ideonella sakaiensis MHETase bound to a substrate | Nature Communications (nature.com)
Free D -amino acids produced by commensal bacteria in the colonic lumen | Scientific Reports
Free D -amino acids produced by commensal bacteria in the colonic lumen | Scientific Reports (nature.com)
Incremental Multiple Sequence Alignment | SpringerLink
Incremental Multiple Sequence Alignment | SpringerLink (link.springer.com)
Higher Level Phylogeny and the First Divergence Time Estimation of Heteroptera (Insecta: Hemiptera) Based on Multiple Genes
Higher Level Phylogeny and the First Divergence Time Estimation of Heteroptera (Insecta: Hemiptera) Based on Multiple Genes (journals.plos.org)
Genetic variation and geographic differentiation in the marine triclad Bdelloura candida (Platyhelminthes, Tricladida, Maricola...
Genetic variation and geographic differentiation in the marine triclad Bdelloura candida (Platyhelminthes, Tricladida, Maricola... (link.springer.com)
Zika virus evolution and spread in the Americas | Nature
Zika virus evolution and spread in the Americas | Nature (nature.com)
Pan-Neuronal Expression of APL-1, an APP-Related Protein, Disrupts Olfactory, Gustatory, and Touch Plasticity in Caenorhabditis...
Pan-Neuronal Expression of APL-1, an APP-Related Protein, Disrupts Olfactory, Gustatory, and Touch Plasticity in Caenorhabditis... (jneurosci.org)
Macrophage migration inhibitory factor of Syrian golden hamster shares structural and functional similarity with human...
Macrophage migration inhibitory factor of Syrian golden hamster shares structural and functional similarity with human... (nature.com)
The archaebacterial origin of eukaryotes | PNAS
The archaebacterial origin of eukaryotes | PNAS (pnas.org)
Frontiers | The Small Giant Clam, Tridacna maxima Exhibits Minimal Population Genetic Structure in the Red Sea and Genetic...
Frontiers | The Small Giant Clam, Tridacna maxima Exhibits Minimal Population Genetic Structure in the Red Sea and Genetic... (frontiersin.org)
Infographic: Resurrecting Ancient Proteins | The Scientist Magazine®
Infographic: Resurrecting Ancient Proteins | The Scientist Magazine® (the-scientist.com)
Non-approximability of Weighted Multiple Sequence Alignment | SpringerLink
Non-approximability of Weighted Multiple Sequence Alignment | SpringerLink (link.springer.com)
Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite...
Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite... (pnas.org)
CiteSeerX - Citation Query The dependence of amino acid pair correlations on structural environment
CiteSeerX - Citation Query The dependence of amino acid pair correlations on structural environment (citeseer.ist.psu.edu)