Title: A Research on Bioinformatics Prediction of Protein Subcellular Localization. VOLUME: 4 ISSUE: 3. Author(s):Gang Fang, Guirong Tao and Shemin Zhang. Affiliation:Department of Life Science, Xian University of Arts and Science, Xian 710065, China.. Keywords:Bioinformatics, prediction, protein subcellular localization, localizome, proteomics, database. Abstract: Protein subcellular localization is one of the key characteristic to understand its biological function. Proteins are transported to specific organelles and suborganelles after they are synthesized. They take part in cell activity and function efficiently when correctly localized. Inaccurate subcellular localization will have great impact on cellular function. Prediction of protein subcellular localization is one of the important areas in protein function research. Now it becomes the hot issue in bioinformatics. In this review paper, the recent progress on bioinformatics research of protein subcellular localization and its prospect ...
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When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. The past 15 years have been exciting ones in plant biology. 1409 análises. 107. 0. Tools covered: If youre not familiar with this, something like https://learn.saylor.org/course/bio101 might be helpful. Page 3/31. We can use a cherry picking approach to explore individual genes in those lists but its nice to be able to have an automated way of analyzing them. 4.7 (1,305) 87k estudiantes. Bioinformatic Methods I. 4.7 (1,538) 96k étudiants Beginner. (2019). 0. Using Gene Ontology enrichment analysis and pathway visualization tools can help us make sense of our own omics experiments and answer the question what processes/pathways are being perturbed in our mutant of interest? Plant Bioinformatic Methods Specialization Coursera Issued Sep 2020. The first part, Bioinformatic Methods I (this one), deals with databases, Blast, multiple sequence ...
Journal of Integrative Bioinformatics (JIB) is an international open access journal publishing original peer-reviewed research articles in all aspects of integrative bioinformatics. Molecular biology produces huge amounts of data in the post-genomic era. This includes data describing metabolic mechanisms and pathways, structural genomic organization, patterns of regulatory regions; proteomics, transcriptomics, and metabolomics. On the one hand, analysis of this data uses essentially the methods and concepts of computer science; on the other hand, the range of biological tasks solved by researchers determines the range and scope of the data. Currently, there are about 1,000 database systems and various analytical tools available via the Internet which are directed at solving various biological tasks. The challenge we have is to integrate these list-parts and relationships from genomics and proteomics at novel levels of understanding. Integrative Bioinformatics is a new area of research using the ...
The 7th International Conference on Bioinformatics and Computational Biology (BICoB) provides an excellent venue for researchers and practitioners in the fields of bioinformatics to present and publish their research results and techniques. Bioinformatics and computational biology continue to be a vibrant research area with broadening applications and new emerging challenges. In recent years, bioinformatics and computational biology have experience significant advances driven by computational techniques in bioinformatics. The BICoB conference seeks original and high quality papers in the fields of bioinformatics, computational biology, systems biology, medical informatics and the related areas. Work in the computational methods related to, or with application in, bioinformatics is also encouraged including: bio-data mining, text mining, machine learning, biomathematics, modeling and simulation, pattern recognition, data visualization, biostatistics, .etc. The topics of interest include (and are ...
Safe and complete genome and metagenome assembly via omnitigs (Alexandru Tomescu). We start by introducing the genome and metagenome assembly problems, and formulate them under the framework of a safe and complete algorithm. We present some previous work on safe algorithms, such as assembling unitigs and Y-to-V contigs. We then give safe and complete algorithms for the two problems. These are based on graph-theoretic characterizations. We conclude by showing some experimental results.. Slides Safe and complete genome and metagenome assembly via omnitigs. Error correction of sequencing reads (Leena Salmela). We will start by discussing the error characteristics of modern sequencing technologies and by introducing the sequencing error correction problem. We will then give an overview of the techniques used for correcting sequencing errors in short read data. The second half of the lecture will discuss methods for correcting the newer long read data with high error rate.. Slides Error ...
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.
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.
Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, youll learn how to use freely available open source tools to extract meaning from large complex biological data sets. At no other point in human history has our ability to understand lifes complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, youre ready to get started. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, ...
Bioinformatics combines computer science and biology to diagnose diseases and analyze complex biological data. Engineers and data scientists at Southwest Research Institute collaborate with biomedical researchers to develop complex bioinformatics data analysis. We help industry partners to innovate in the areas of Computational Biomedicine with automated cancer detection,
We may wonder that as a biologist why should we learn algorithms, which are intended for computer science. The answer is straightforward. The convergence of Biology and computer science is called as BIOINFORMATICS. To be a real Biologist we have to acquire skills in Biology as well as in computer science. Biological skills include Cell life cycle, double helix structure of DNA, Transcription, and Translation and down the line. In Computer Science, we should learn about how to write efficient computer program for solving BioInformatics problems. In this point I like to remember that one of the man (Crick) who finds the DNA double Helix structure is not a Biologist but he is a physicist. ...
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Andreas Beyer, Michael Schroeder (Eds.): Proceedings of the German Conference on Bioinformatics, GCB 2008, September 9-12, 2008, Dresden, Germany. LNI 136 GI 2008 ...
Course Catalogue > PřF:C3210 Structural bioinformatics - Course Information. Registration closes on the 7th August 2015. Date: Topics: Asgmt: Lecturer: 1: 14 Mar 2011: Introduction and overview : no: JP, EE: 2: 21 Mar 2011 The course provides in-depth training of all major structural molecular biology techniques including its applications in drug discovery. Generally speaking, projects should propose a method for solving a specific problem and then evaluate how well the method performs on a structural data set. Assignments performed during the Structural Bioinformatics course, at the University of Copenhagen. It should be a credible investigation of a research problem in structural bioinformatics. We will then elucidate the biochemical and structural basis for the phenotype caused by the mutant protein. Bourne, … 2036 Palmer Commons Bldg. Structural bioinformatics (Methods of biochemical analysis, v.44). Structural Bioinformatics Second Semester 2011 Course Syllabus. Structural Bioinformatics ...
We supply infrastructure and expertise for the bioinformatics and scientific IT needs of researchers, providing hardware and software for research-oriented tasks. We have various web-based interactive tools at our disposal, e.g. a local copy of the UCSC (University of California, Santa Cruz) Genome Browser, Shiny Server for interactive analysis, and an internal Galaxy server. We also have access to bioinformatics software solutions such as methylKit, genomation, RCAS, netSmooth, and a GNU Guix bioinformatics software repository.. We provide additional specialized IT services geared towards bioinformatics end users as well as a mobile teaching system for scientists. In addition, we offer courses and consultation sessions on bioinformatics, IT skills, and programming.. We provide additional specialized IT services geared towards bioinformatics end- users as well as a mobile teaching system for scientists. In addition, we offer courses and consultation sessions on bioinformatics, IT skills, and ...
DISCRETE APPLIED MATHEMATICS CALL FOR PAPERS FOR THE COMPUTATIONAL MOLECULAR BIOLOGY SERIES We are happy to announce that our collection of Special Issues on Computational Molecular Biology has become the ,,Computational Molecular Biology Series,,, an ongoing regular feature of Discrete Applied Mathemtaics. Series Editors: Sorin Istrail, Pavel Pevzner, Ron Shamir Submission Deadline for the next volume: August 1, 1998 Dont ask [only] what mathematics can do for biology, ask what biology can do for mathematics. Stanislaw Ulam Manuscripts are solicited for a volume of Discrete Applied Mathematics on topics concerning the development of new combinatorial and algorithmic techniques in computational molecular biology. This volume will be the third in the Computational Molecular Biology Series of Discrete Applied Mathematics, which publishes papers on the mathematical and algorithmic foundations of the inherently discrete aspects of computational biology. The refereeing of the papers in this ...
Genomics-based drug discovery utilizing sequencing data for elucidation of candidate targets has led to the development of a number of successful treatments in the last decades. However, the molecular driver signals for many complex diseases cannot be easily derived from genome sequencing. Functional profiling studies, such as those involving the detection of protein interaction networks or the effects of perturbations with small molecules or siRNAs on cellular phenotypes, offer a complementary approach for the identification of molecular vulnerabilities that can be exploited in the development of new treatment strategies. The goal of this thesis was to develop computational systems biology methods for supporting such functional endeavors, and through their application use cases, to elucidate novel disease driver signals in cancer and Alzheimers disease networks. The availability of functional profiling data (such as biochemical target selectivity information or efficacy readouts) for numerous ...
A brief Biography: Dr Andrey Kajava holds a position of Director of Research at the Centre National de la Recherche Scientifique (CNRS) in France. He is a head of Structural Bioinformatics and Molecular Modeling group at the Centre de Recherche de Biochimie Macromoléculaire (Montpellier, France). In the past, he conducted research in several prestigious laboratories in Russia, Germany, Belgium, Switzerland and United States. His group is using methods of theoretical structural biology and bioinformatics to understand principles of protein structures and biomolecular interactions. The obtained knowledge is applied for prediction of protein structures and functions, drug design, as well as for de novo design of proteins. Topics of our particular interest are: proteins with tandem repeats, amyloids and prions. The results of his work can be applied in materials science, biotechnology, nanotechnology and medicine.. ...
Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein sequence and structure to gene expression data. Here we present the CombFunc web server, which makes Gene Ontology (GO)-based protein function predictions. CombFunc incorporates ConFunc, our existing function prediction method, with other approaches for function prediction that use protein sequence, gene expression and protein-protein interaction data. In benchmarking on a set of 1686 proteins CombFunc obtains precision and recall of 0.71 and 0.64 respectively for gene ontology molecular function terms. For biological process GO terms precision of 0.74 and recall of 0.41 is obtained. ...
With the remarkable increase of microbial and viral sequence data obtained from high-throughput DNA sequencers, novel tools are needed for comprehensive analysis of the big sequence data. We have developed
With your expertise in computational biology, you contribute input to experimental design, quality control, basic and downstream analysis of single cell RNA-Seq data. You generate results from computational biology analysis such as single cell RNA-Seq related algorithms, pathway analysis, biomarker analyses, gene prioritization, etc. Moreover, you keep track of relevant literature and integrate publicly available relevant datasets that can enhance the interpretation of the results. Participating in the publication of results in peer-reviewed journals and at scientific congresses is also your task. You are also responsible for interfacing with collaborators in the ICL and BI experimental groups as well as the ICL and BI computational biology groups.
Whos your neighbor? New computational approaches for functional genomics? Large-scale functional analysis using peptide or protein arrays
Genomics, Bioinformatics and Computational Biology: we do genomics and bioinformatics data analysis on genome sequences. And we developped a novel computational algorithms, Codon and Amino acid Unified Sequence Alignment (CAUSA), and a set of user-friendly computer programs for molecular evolutionary analysis, which revealled some novel mechanisms for molecular evolution, such as codon splitting, codon fusion and InDel-induced partial frameshifting ...
Bioinformatics community open to all people. Strong emphasis on open access to biological information as well as Free and Open Source software.
Chemoresistance is a major limitation for breast cancer therapy. In the present study, bioinformatics analyses were performed to investigate microRNA (miRNA)-mediated mechanism of breast cancer chemoresistance and to identify molecular targets. In the present study, we identified 22 DE-miRNAs in chemoresistant breast cancer and chemosensitive tissues based on the GEO database GSE71142. Then, by the target gene software of miRWalk2.0, we identified the potential target genes of these chemoresistance-related miRNAs. The enrichment and function analyses showed that these target genes may participate in many important cancer-related biological processes, molecular functions and signaling pathways.. Among the dysregulated miRNAs, miR-196a-5p (upregulation) and miR-4472 (downregulation) were found to have the greatest expression fold change between chemoresistant and chemosensitive tissues. miR-196a-5p has been previously reported to be overexpressed in triple-negative breast cancer compared with ...
Computational Biology & Bioinformatics Team: Currently 2 senior research scientists (Joohyun Kim and Nayong Kim) focused on assisting bioinformatics and broader computational biology efforts, especially in connection with LBRN = Louisiana Biomedical Research Network. CCT search underway to hire a Senior Bioinformatics Computational Scientist Software tools. ...
The Fulbright Program in Ukraine is pleased to invite you to a seminar Total Synthesis of Natural Products as a Driving Force for Chemical and Biological Discovery by Fulbright Ph.D. student 2011-2016 Nataliia Shymanska, to be held on Tuesday, December 1, 2015, 6:00 p.m., at the Fulbright Office (20 Esplanadna Street, Suite 904, M Palats Sportu, Kyiv).. Total Synthesis of Natural Products as a Driving Force for Chemical and Biological Discovery. Untreatable infections, a result of multi-drug resistance of pathogenic bacteria (Enterococcus spp., Staphylococcus aureus, Pseudomonas aeruginosa etc.) to antibiotics, continue to be a major threat to public health and modern medicine.. The numbers are alarming: out of 400,000 instances of infections caused by resistant pathogens 25,000 were lethal (Europe, 2007); 54% of isolated bacterial strains of Staphylococcus Aureus from Ukrainian hospitals in 2010 were resistant to antimicrobial treatments.. Despite the world-wide pressing clinical need, the ...
The target audience is upper-year undergraduate students in the biological sciences, or biology graduate students who are just beginning their studies and need a refresher on some of the topics mentioned above. Computer scientists who are interested in biology might also find this course useful - the biology isnt too complex.. After finishing Bioinformatic Methods II, students will be familiar with databases and tools for exploring patterns in proteins and promoters, analyzing protein-protein interaction networks as well as protein tertiary structures, and using gene expression databases to make hypotheses. Bioinformatic Methods I provides further practical approaches for sequence analysis.. Do you teach the same course to students on campus? If so, in what ways does the MOOC version differ from on-campus version ...
Many vital biological processes, including transcription and splicing, require a combination of short, degenerate sequence patterns, or motifs, adjacent to defined sequence features. Although these motifs occur frequently by chance, they only have biological meaning within a specific context. Identifying transcripts that contain meaningful combinations of patterns is thus an important problem, which existing tools address poorly. Here we present a new approach, Fast-FIND (Fast-F ully I ndexed N ucleotide D atabase), that uses a relational database to support rapid indexed searches for arbitrary combinations of patterns defined either by sequence or composition. Fast-FIND is easy to implement, takes less than a second to search the entire Drosophila genome sequence for arbitrary patterns adjacent to sites of alternative polyadenylation, and is sufficiently fast to allow sensitivity analysis on the patterns. We have applied this approach to identify transcripts that contain combinations of sequence motifs
|i| Computational Biology and Bioinformatics (CBB) |/i| aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of computational biology and bioinformatics. The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology.
Immunoinformatics involves the application of computational methods to immunological problems. Prediction of B- and T-cell epitopes has long been the focus of immunoinformatics, given the potential translational implications, and many tools have been developed. With the advent of next-generation sequencing (NGS) methods, an unprecedented wealth of information has become available that requires more-advanced immunoinformatics tools. Based on information from whole-genome sequencing, exome sequencing and RNA sequencing, it is possible to characterize with high accuracy an individual’s human leukocyte antigen (HLA) allotype (i.e., the individual set of HLA alleles of the patient), as well as changes arising in the HLA ligandome (the collection of peptides presented by the HLA) owing to genomic variation. This has allowed new opportunities for translational applications of epitope prediction, such as epitope-based design of prophylactic and therapeutic vaccines, and personalized cancer immunotherapies
Graduate Group in Bioinformatics seeks a second renewal of its training program in Bioinformatics and Computational Biology. The program focuses on training you...
Focuses on bioinformatics and its importance in the sciences. Seeks to apply and understand bioinformatics tools as they pertain to analyses of genomes, protein structure/function, gene families, and molecular evolution. Uses bioinformatics tools to mine databases for information relevant to answering questions relating to molecular structure, function, and evolution. Analyzes relationships between known protein structure and model protein structures. Illustrates how multiple alignments and database searching are used to gather data about gene sequences. Describes how to identify genes and infer gene structure. Differentiates between the types of phylogenetic analyses available and appropriate programs for specific questions. Applies students’ existing content knowledge toward practical bioinformatic applications Offers students an opportunity to develop skills in analysis, problem solving, and communication as applied to bioinformatics ...
The cell cycle, with its highly conserved features, is a fundamental driver for the temporal control of cell growth and proliferation in tissues - while abnormal control and modulation of the cell cycle are characteristic of cancer cells, particularly in response to therapy. A central theme in cancer biology is to resolve and understand the origin and nature of innate and induced heterogeneity at the cell population level. Cellular heterogeneity - comprising structural, temporal and functional dimensions - is a confounding factor in the analysis of cell population dynamics and has implications at physiological, pathological and therapeutic levels. There is an exceptional advancement in the applications of imaging and cell tracking technologies dedicated to the area of cytometric research, that demand an integrated bioinformatics environment for high-content data extraction and interrogation. Image-derived cell-based analyses, where time is the quality parameter also demand unique solutions with ...
BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all ...
Bioinformatics community open to all people. Strong emphasis on open access to biological information as well as Free and Open Source software.
ZENBU, a new, freely available bioinformatics tool developed at the RIKEN Center for Life Science Technology in Japan, enables researchers to quickly and easily integrate, visualize and compare large amounts of genomic information resulting from large-scale, next-generation sequencing experiments. Next-generation sequencing has revolutionized functional genomics, with protocols such as RNA-seq, ChIP-seq and CAGE being used widely around the world. The power of these techniques lies in the fact that they enable the genome-wide discovery of transcripts and transcription factor binding sites, which is key to understanding the molecular mechanisms underlying cell function in healthy and diseased individuals and the development of diseases like cancer. The integration of data from multiple experiments is an important aspect of the interpretation of results, however the growing number of datasets generated makes a thorough comparison and analysis of results cumbersome. In a report published today in the
Genomics and Computational Biology is an open access on-line scientific publication. The journal is focused on bioinformatic approaches aiming to understand genome biology and also covers more general aspects of computational biology/bioinformatics.
Profile: The Biomedical Research Center (CINBIO) offers two full-time interim postdoctoral positions to highly motivated and qualified researchers on developing novel applications and tools in health domain using NLP and ABM techniques, related to the area of Bioinformatics, in the SI-04 group (SING, Sistemas Informáticos de Nueva Generación), based in Ourense.. Time frame: initially for 3.5 months for both positions (starting on may 2019), and may be continued.. Call: information for candidates, and how to apply for the post. Application deadline: 25th March 2019 (12:00 hours, local time). Published also here:: https://euraxess.ec.europa.eu/jobs/385099. 4apr2019:. The Evaluation Board publishes the CINBIO-32-33-Postdoctoral-SING-Evaluation Resolution. There is a period of five days for claims (until 10abr2018, 14:00H).. Evaluation criteria:. ...
The availability of immunome-mining tools has fueled the design and development of vaccines by a process that was at first called vaccinomics by Brusic and Petrovsky in 2002, reverse vaccinology by Rappuoli in 2003 and, more recently, immunome-derived or genome-derived vaccine design by Pederson; De Groot and Martin; and Doytchinova, Taylor, and Flower.. The theory behind these descriptors is that a minimal set of antigens that induce a competent immune response to a pathogen or neoplasm can be discovered using immunoinformatics, and that administration of these epitopes, in the right delivery vehicle and with the correct adjuvant, will result in a degree of protection against infection by the pathogen. In its most minimalist form, an IDV would contain only adjuvanted B-cell and T-cell epitopes in delivery vehicles such as liposomes. When these minimal components are packaged in an appropriate delivery vehicle, the complete package comprises an immunome-derived vaccine.. Compared to ...
Bioinformatics is the application of information technology (informatics) to biological data. Informatics is the representation, organization, manipulation, distribution, maintenance, and use of digital information. When applied to biological data, informatics provides databases and analytical tools for answering biological questions. Bioinformatics is inherently interdisciplinary, involving aspects of biology, computer science, mathematics, physics, and chemistry. While computers have been used to analyze biological data since their invention, the need for computational methods has recently exploded due to the huge amounts of data produced by genome sequencing projects and other high-throughput technologies. Bioinformatics techniques are being used to move the field of biology from a one gene at a time approach, to the analysis of whole systems. In this course, students will learn current bioinformatics techniques to address systems-level biological questions. Topics include sequence ...
Bioinformatics is the application of information technology (informatics) to biological data. Informatics is the representation, organization, manipulation, distribution, maintenance, and use of digital information. When applied to biological data, informatics provides databases and analytical tools for answering biological questions. Bioinformatics is inherently interdisciplinary, involving aspects of biology, computer science, mathematics, physics, and chemistry. While computers have been used to analyze biological data since their invention, the need for computational methods has recently exploded due to the huge amounts of data produced by genome sequencing projects and other high-throughput technologies. Bioinformatics techniques are being used to move the field of biology from a one gene at a time approach, to the analysis of whole systems. In this course, students will learn current bioinformatics techniques to address systems-level biological questions. Topics include sequence ...
Information on vertebrate proteins (mainly those from mouse and human) that are thought to, or known to, be localised to the cell nucleus. Where known, the sub-nuclear compartment where the proteins have been found are reported. Also stored is information on the amino acid sequence, predicted protein size and isoelectric point, as well as any repeats, motifs or domains within the protein sequence. Biological and molecular functions of the proteins are described using GO terms.. ...
Overview. Bioinformatics has become an essential component of computationally intensive functional genomics, comparative genomics, gene discovery, transcriptional regulatory networks, biochemical pathway analysis, molecular modeling, proteomics and rational drug design. It helps to analyze genes on a massive scale to dissect the precise understanding of the biological processes at the molecular level. Bioinformatics is widely regarded as the key to decipher the staggering functional genomics and genotyping data in the 21st century.. Envisaging the potential of bioinformatics in modern biological research, KBIRVO, SankaraNethralaya established Center for Bioinformatics by 2010, to provide a platform for education and research in bioinformatics and its application to Vision Science. The ultimate goal of this multidisciplinary center is to focus on research and education in the rapidly emerging fields of bioinformatics and computational biology which deal with the analysis, integration and ...
Bioinformatics Algorithms (Part 1) with Pavel Pevzner, Phillip E. C. Compeau,. The course Bioinformatics Algorithms (Part 1) by Pavel Pevzner, Phillip E. C. Compeau, and Nikolay Vyahhi from University of California, San Diego will be offered free of charge to everyone on the Coursera platform. Sign up at http://www.coursera.org/course/bioinformatics. ...
Database of compound genetic marker called SNPSTR which combines a STR marker with one or more tightly linked SNPs. Here, the SNP(s) and the microsatellite are less than 250 base pairs apart so each SNPSTR can be considered a small haplotype with no recombination occurring between the two individual markers.. ...
Welcome to the official website of the 2012 International Conference on Bioinformatics and Computational Biology, BIOCOMP BG 2012, which will be held in Varna, Bulgaria, during the period of September 20-21, 2012. There will be a strong focus on the bioinformatics challenges, arising from the extraordinary developments in high throughput technologies. BIOCOMP BG 2012 aims to bring researchers, scientists, engineers, and scholar students together so they can exchange and share their experiences, new ideas and research results about all aspects of Bioinformatics and Computational Biology, as well as to discuss the practical challenges they have encountered and the solutions adopted to solve them ...
Hofestädt, R., and Kolchanov, N. eds. (2010). Computational Systems Biology: German/Russian Network of Computational Systems Biology. Medizinische Informatik und Bioinformatik ...
In one of the first major texts in the emerging field of computational molecular biology, Pavel Pevzner covers a broad range of algorithmic and combinatorial topics and shows how they are connected to molecular biology and to biotechnology. The book has a substantial computational biology without formulas component that presents the biological and computational ideas in a relatively simple manner. This makes the material accessible to computer scientists without biological training, as well as to biologists with limited background in computer science. Computational Molecular Biology series: computer science and mathematics are transforming molecular biology from an informational to a computational science. Drawing on computational, statistical, experimental, and technological methods, the new discipline of computational molecular biology is dramatically increasing the discovery of new technologies and tools for molecular biology. The new MIT Press Computational Molecular Biology series ...
Bioinformatics, Biomedicine, Biotechnology and Computational Biology scheduled on November 09-10, 2020 in November 2020 in Dubai is for the researchers, scientists, scholars, engineers, academic, scientific and university practitioners to present research activities that might want to attend events, meetings, seminars, congresses, workshops, summit, and symposiums.
World Conference Calendar, ICBCB 2012, aims to bring together researchers, scientists, engineers, and scholar students to exchange and share their experiences, new ideas, and research results about all aspects of Bioinformatics and Computational Biology, and discuss the practical challenges encountered and the solutions adopted. The conference will be held every year to make
Far-reaching biological achievements, epitomized by the Human Genome Project, are the outcome of fast-growing compilations of vast and complex biological information. In order to analyze the plethora of data gathered, Biology requires the aid of computational interpretation - hence, Computational Biology.. The Computational Genomics Laboratory at Tel Aviv Universitys School of Computer Science, has been researching computational problems related to gene, protein and disease analysis. The labs research interests include gene expression analysis, modeling and dissection of molecular networks, gene regulation, genomic rearrangements and cancer genomics. The methodologies assisting the researchers in their analysis are graph theory, complexity, probability and statistics. Methods and software tools developed by the group are in use by many laboratories around the world.. The lab is supervised by: Prof. Ron Shamir.. ...
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Description: The Computational Biology and Bioinformatics Group at the University of Macau is looking for a post-doctoral candidate in the area of computational chemistry or computational biology to participate in an interdisciplinary research project. The key research goal of the project is to study the protein-surface adsorption process on biotechnologically relevant surfaces such as Teflon using coarse-grained molecular dynamics (CGMD) simulations. The work includes modeling of interested system, parameterization, simulation and analysis. Applicants should have knowledge in MD techniques and programming, have received their Ph.D. recently with training in computational chemistry, computational biology or related areas, and a significant track record ...
NEW] Video collection for the 2013 lectures on Next Generation Sequencing Data Analysis is now available in the course website. The video collections for the 2011 lectures on Next Generation Sequencing Data Analysis are now available at Youtube and Youku. The slides can also be downloaded. Please address all the feedback directly to Dr. Yunlong Liu @ [email protected] ...
Call for Papers* 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM16) http://cci.drexel.edu/ieeebibm/bibm2016/ Dec 15-18, 2016, Shenzhen, China, The IEEE International Conference on Bioinformatics and Biomedicine (BIBM) has established itself as the premier research conference in bioinformatics and biomedicine. IEEE BIBM 2016 provides a leading forum for disseminating the latest research in bioinformatics and health informatics. It brings together academic and industrial scientists from computer science, biology, chemistry, medicine, mathematics and statistics. We solicit high-quality original research papers (including significant work-in-progress) in any aspect of bioinformatics and biomedicine. *New computa*t*ional techniques and *me*thods in machine learning; data mining; text analysis; *pa*ttern recognition;* k*nowledge r*epresentation; databases; data modeling; combinatorics; stochastic modeling; string and graph algorithms; linguistic methods; robotics; constraint ...
Background: Variants in transcription factor binding sites (TFBSs) may have important regulatory effects, as they have the potential to alter transcription factor (TF) binding affinities and thereby affecting gene expression. With recent advances in sequencing technologies the number of variants identified in TFBSs has increased, hence understanding their role is of significant interest when interpreting next generation sequencing data. Current methods have two major limitations: they are limited to predicting the functional impact of single nucleotide variants (SNVs) and often rely on additional experimental data, laborious and expensive to acquire. We propose a purely bioinformatic method that addresses these two limitations while providing comparable results. Results: Our method uses position weight matrices and a sliding window approach, in order to account for the sequence context of variants, and scores the consequences of both SNVs and INDELs in TFBSs. We tested the accuracy of our method ...
PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online. We aim to simulate the classroom experience as closely as possible, with opportunities for one-to-one discussion with tutors and a focus on interactivity throughout. InterMine is a freely available open-source data warehouse built specifically for the integration and analysis of complex biological data. InterMine-based data analysis platforms are available for many organisms including mouse, rat, budding yeast, plants (over 87 plant genomes), nematodes, fly, zebrafishHymenoptera, Planaria, and more recently human. Genomic and proteomic data within InterMine databases includes pathways, gene expression, interactions, sequence variants, GWAS, regulatory data and protein expression. InterMine provides sophisticated query and visualisation tools both through a web interface and a powerful web service API, with multiple language bindings including Python and R. This course will focus on the InterMine web interface ...
2013) Delivering intellectual physical download computational systems biology inference and modelling 2016 in Russian events: a weight mass of Scottish Natural Heritage National Nature Reserves. International Research in Geographical and Environmental Education, multiperiod), 4-22. The Canadian Environmental Literacy Project( CELP).
Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD) in the world. Emerging evidence has shown that urinary mRNAs may serve as early diagnostic and prognostic biomarkers of DKD. In this article, we aimed to first establish a novel bioinformatics-based methodology for analyzing the
This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include: Genomes: biological sequence analysis, hidden Markov models, gene finding, RNA folding, sequence alignment, genome assembly Networks: gene expression analysis, regulatory motifs, graph algorithms, scale-free networks, network motifs, network evolution Evolution: comparative genomics, phylogenetics, genome duplication, genome rearrangements, evolutionary theory, rapid evolution
To see the scholarly work done by the Bioinformatics and Computational Biology program: visit the Iowa State University Digital Repository click on a person and then their Google Scholar link Bioinformatics and Computational Biology theses and dissertations
DNASTAR NovaFold is protein structure prediction software that is based on I-Tasser, the award-winning software package developed by Prof. Yang Zhangs laboratory at the University of Michigan. NovaFold utilizes the I-Tasser algorithms developed by Prof. Zhang that combine threading and ab initio folding technologies to build accurate, full 3D atomic models of proteins with previously unknown structures.
Rationale: Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. Objective: The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and Web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. Methods and results: We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB; www.HeartProteome.org), a centralized platform of high-quality cardiac proteomic data, bioinformatics tools, and relevant cardiovascular phenotypes. Currently, COPaKB features 8 organellar modules, comprising 4203 LC-MS/MS experiments from human, mouse, drosophila, and Caenorhabditis elegans, as well as expression images of 10 924 proteins in ...
After the expression of the titin-Hsp27-construct with the following purification supplies no satisfied results which makes the realization of the atomic force microscopy not possible. The devel-opment of the structure model by using different bioinformatic methods can establish a model for the protein sequence. As bioinformatic methods the template search by different BLAST runs and free available software like SwissModel, Pcons, ModWeb and other tools are used. Nevertheless, the generated model is not the native conformation and has to be analyzed with other software until a stable conformation of the structure can be predicted. Depending on the time which is provided the generated model is a good approach for the aim this master thesis has ...
After the expression of the titin-Hsp27-construct with the following purification supplies no satisfied results which makes the realization of the atomic force microscopy not possible. The devel-opment of the structure model by using different bioinformatic methods can establish a model for the protein sequence. As bioinformatic methods the template search by different BLAST runs and free available software like SwissModel, Pcons, ModWeb and other tools are used. Nevertheless, the generated model is not the native conformation and has to be analyzed with other software until a stable conformation of the structure can be predicted. Depending on the time which is provided the generated model is a good approach for the aim this master thesis has ...
Nov. 17, 2001. Clustering Protein Sequences Structure Prediction by Transitive Homology. Alexander Schliep at In Silico Biology: Bioinformatics after the Human Genome. The Third Georgia Tech-Emory International Conference on Bioinformatics, GA (Invited Talk) Nov. 14, 2001. Automated visualization of graph algorithms. Alexander Schliep at Computer Science Education Seminar, Georgia Institute of Technology, GA (Invited Talk) Nov. 8, 2001. An efficient algorithm for selecting target-specific probes for DNA arrays. Alexander Schliep at Berkeley Drosophila Genome Project, University of California at Berkeley & Lawrence Berkeley National Laboratory, CA (Invited Talk) Nov. 7, 2001. A Bayesian approach to learning Hidden Markov Model topology. Alexander Schliep at Department of Computer Engineering, University of California at Santa Cruz, CA (Invited Talk) Nov. 5, 2001. Outperforming PSI-Blast on the search for remote homologues. Alexander Schliep at Computational Genomics Group, University of ...
Activities report of the Bioinformatics service - update at March 2019. BIOINforMA is taking care of implementing software, website and databases and maintaining HPC service for SZN people. The maintenance of the HPC began in May 2017. The bioinformatics services began in July 2018. Since then we received 45 official independent requests. 32 were successfully solve and 13 are in progress.. Activities and products: Web based platforms:. ...
MiRNAs are frequently abnormally expressed in the progression of human osteosarcoma. Phosphatase and tensin homologue deleted on chromosome 10 (PTEN) is one of the tumor suppressors in various types of human cancer. In the present study, we detected how hsa-miR-30a-3p regulated PTEN and further tested the role of hsa-miR-30a-3p in the cell proliferation of osteosarcoma cells. The levels of miR-30a were determined by real time PCR. The expression of PTEN was tested by western blotting analysis. Cell distribution of PTEN was observed with confocal laser scanning microscope. Cell viability was determined by MTT assay. The expression of miR-30a and PTEN was obviously decreased in MG-63, 143B and Saos-2 cells compared with primary osteoblasts. TargetScan analysis data showed miR-30a might bind with position 30-57 of 3UTR of PTEN. Transfection with miR-30a-3p increased the level of PTEN in MG-63 cells, while transfection with miR-30a-3p inhibitor significantly decreased the expression of PTEN in osteosarcoma
Thesis Defense. Title: Computational Detection of Driver Mutations in Cancer Genomes. Abstract: Cancer is caused largely by the accumulation of somatic mutations during the lifetime of an individual. Recent advances in next generation sequencing (NGS) enable measurement of somatic mutations in a cohort of samples. Large-scale cancer sequencing projects like The Cancer Genome Atlas (TCGA) have generated a huge amount of somatic mutations in thousands of tumors. This thesis addresses two challenges. The first challenge is to distinguish driver mutations that are responsible for cancer development from passenger mutations, random events that do not contribute to the cancer phenotype in a cohort of samples. This is a difficult problem because most somatic mutations measured in tumor samples are passenger mutations, and only a small portion of these mutations are driver mutations. The second challenge is to accurately identify larger genomic variants, also known as structural variants (SV), one type ...
Corresponding author. Separate names of authors from the text below by one blank line.. Key words: use 12-point Times New Roman in Italics.. Separate key words from the text below by one blank line.. The text is divided into sub-sections under the following headings: Motivation and Aim; Methods and Algorithms; Results, Conclusion and Availability; References (if necessary). All these words should be typed in Italics. In cases where authors feel the headings inappropriate, some flexibility is allowed. The abstracts should be succinct and contain only the material relevant to the headings. If internet hyperlinks are available for any part of the abstract, then this should be given in the form of clickable text, i.e.{{http://www...}}.. ...
To exert regulatory function, miRNAs guide Argonaute (AGO) proteins to partially complementary sites on target RNAs. Crosslinking and immunoprecipitation (CLIP) assays are state-of-the-art to map AGO binding sites, but assigning the targeting miRNA to these sites relies on bioinformatics predictions and is therefore indirect. To directly and unambiguously identify miRNA:target site interactions, we modified our CLIP methodology in C. elegans to experimentally ligate miRNAs to their target sites. Unexpectedly, ligation reactions also occurred in the absence of the exogenous ligase. Our in vivo data set and reanalysis of published mammalian AGO-CLIP data for miRNA-chimeras yielded ∼17,000 miRNA:target site interactions. Analysis of interactions and extensive experimental validation of chimera-discovered targets of viral miRNAs suggest that our strategy identifies canonical, noncanonical, and nonconserved miRNA:targets. About 80% of miRNA interactions have perfect or partial seed complementarity. ...
The Organizing committee of BGRS\SB-2012 cordially invites sponsorship for the conference, which will be held on June 25-29, 2012. We offer the different sponsorship opportunities.. For example, your organization or company name and logo will appear on BGRS\SB-2012 web-site. We can acknowledge your sponsorship in internationally distributed Proceedings of the conference. At the conference, providers of corporate sponsorship may have speakers, presentation booth, and so on…. If you wish to be sponsor or co-sponsor of BGRS\SB-2012, please contact us through e-mail [email protected] for more details.. ...
Wassan, J. T., Zheng, H., Wang, H., Browne, F., Walsh, P., Manning, T., Dewhurst, R. & Roehe, R., Nov 2019, Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019. Yoo, I., Bi, J. & Hu, X. T. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 1900-1906 7 p. 8983040. (Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019).. Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review ...
One consequence of increasing sequencing capacity is the the accumulation of \textit{in silico} predictions in biological sequence databanks. This amount of data exceeds human curation capacity and, despite methodological progress, numerous errors on the prediction of protein functions are made. Therefore, tools are required to guide human expertise in the evaluation of bioinformatics predictions taking into account background knowledge on the studied organism.. GROOLS (for Genomic Rule Object-Oriented Logic System) is an expert system that is able to reason on incomplete and contradictory information. It was developed with the objective of assisting biologists in the process of genome functional annotation by integrating high quantity of information from various sources. GROOLS adopts a generic representation of knowledge using a directed acyclic graph of concepts that represent the different components of a biological process (e.g. a metabolic pathway) connected by two types of relations ...
Subcellular localisation prediction in high-quality scientific databases and software tools using Expasy, the Swiss Bioinformatics Resource Portal.
Gaurav Kandoi, a BCB Ph.D. candidate in Julie Dickersons lab will be presenting a paper at a November 13-16 conference in Kansas City, Missouri. The paper is entitled, Differential alternative splicing patterns with differential expression to computationally extract plant molecular pathways.. The conference is the IEEE International Conference on Bioinformatics and Biomedicine, and Gaurav will present at one of the workshops associated with the conference entitled The 8th Integrative Data Analysis in Systems Biology. ...
Head of Bioinformatics Employer Servier Location Croissy-sur-Seine, Chatou (FR) Salary Undisclosed Posted September 08 2016 Ref W-009249 Discipline Life Sciences, Bioinformatics Send Save Apply Head of Department Bioinformatics & Computational Biology. In order to successfully meet the challenges presented by large- scale omics data in biomedical research, we are actively seeking a highly motivated and experienced leader to head the Department of Bioinformatics & Computational Biology.. We indeed offer an exceptional opportunity, to further develop an existing team focused on analysis of genomics & proteomics data coupled with bioinformatics & computational analysis. The position is of highest importance to support biomarker, target discovery & validation and translational research in multiple therapeutic areas, notably oncology.. Our working spirit is based on entrepreneurship, collaboration, result orientation and communication.. Key roles and activities:. a team of bioinformaticians, you ...
We are the Providers of Genome Analysis Software , Protein structure prediction tool, In-sillico Drug design software, drug discovery, Bioinformatics, Bioinformatics, algorithms for Genome analysis, active site directed Drug Design, gene to drug, Bioinformatics and computational Biology facility, super computer access, research and development in bioinformatics, computational pathways for life sciences in India
Computational Genomics. Lecture 1, Tuesday April 1, 2003. Biology in One Slide. High Throughput Biology. DNA Sequencing. …ACGTGACTGAGGACCGTG CGACTGAGACTGACTGGGT CTAGCTAGACTACGTTTTA TATATATATACGTCGTCGT ACTGATGACTAGATTACAG ACTGATTTAGATACCTGAC TGATTTTAAAAAAATATT…. High Throughput...
Posters should be put on display on Wednesday, 11 September, in the morning. Tacks for putting up the posters will be provided onsite.. Posters will be presented during the poster session on Wednesday, 11 September.. ...
The Applied Computational Genomics group focuses on theoretical and computational aspects of modelling the process of genome evolution and adaptive change.
C a l l f o r P o s t e r s 2nd International Conference on Bioinformatics Research and Development BIRD08 www.birdconf.org Technical University of Vienna, Austria July 7 -- 9, 2008 Scope of the conference: The primary focus of BIRD 08 is to provide researchers and users in the field of bioinformatics a forum in which to interact about new research directions, developments, and software/web services. It encompasses the methods of solving biological, medical, or chemical problems by computer science, machine learning, or information processing tools. The conceptual level of the methods range from theoretical approaches through the design of algorithms, models, and information processing systems through to the development of software packages and web services. The program committee seeks contributions, which topics include, but are not limited to: . Algebraic Biology . Databases & Data Integration . Drug Design . Ontologies & Textmining . Evolution and Phylogenetics . Genomics . Gene and Splice ...
Elastic registration in 3D volume data. R. Schilling. Masters Thesis, Universität Freiburg, 2007. [details] Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information. I.G. Costa, M.C.P. de Souto and A. Schliep. In Advances in Bioinformatics and Computational Biology, Proceedings of the Brazilian Symposium on Bioinformatics, Springer Verlag, 81-92, 2007. [details] [pdf] Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data. I.G. Costa, R. Krause, L. Optiz and A. Schliep. BMC Bioinformatics 2007, 8, S3. [details] [pdf] [supp] [PubMed] Gene expression trees in lymphoid development. I. Costa, S. Roepcke and A. Schliep. BMC Immunol 2007, 8:1, 25 . [details] [pdf] [supp] [PubMed] Partially-supervised context-specific independence mixture modeling. B. Georgi and A. Schliep. In workshop on Data Mining in Functional Genomics and Proteomics, ECML 2007, 2007. [details] [pdf] Incomplete and inaccurate ...
Description. This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include: Genomes: biological sequence analysis, hidden Markov models, gene finding, RNA folding, sequence alignment, genome assembly Networks: gene expression analysis, regulatory motifs, graph algorithms, scale-free networks, network motifs, network evolution Evolution: comparative genomics, phylogenetics, genome duplication, genome rearrangements, evolutionary theory, rapid evolution This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We ...
Computational Biology, which includes many aspects of bioinformatics, is the science of using biological data to develop algorithms or models to understand biological systems and relationships. Until recently, biologists did not have access to very large amounts of data. This data has now become commonplace, particularly in molecular biology and genomics. Researchers were able to develop analytical methods for interpreting biological information, but were unable to share them quickly among colleagues.[3] Bioinformatics began to develop in the early 1970s. It was considered the science of analyzing informatics processes of various biological systems. At this time, research in artificial intelligence was using network models of the human brain in order to generate new algorithms. This use of biological data to develop other fields pushed biological researchers to revisit the idea of using computers to evaluate and compare large data sets. By 1982, information was being shared among researchers ...
Non-coding RNAs (ncRNAs) contain both characteristic secondary-structure and short sequence motifs. However, complex ncRNAs (RNA bound to proteins in ribonucleoprotein complexes) can be hard to identify in genomic sequence data. Programs able to search for ncRNAs were previously limited to ncRNA molecules that either align very well or have highly conserved secondary-structure. The RNAmotif program uses additional information to find ncRNA gene candidates through the design of an appropriate descriptor to model sequence motifs, secondary-structure and protein/RNA binding information. This enables searches of those ncRNAs that contain variable secondary-structure and limited sequence motif information. Applying the biologically-based concept of positive and negative controls to the RNAmotif search technique, we can now go beyond the testing phase to successfully search real genomes, complete with their background noise and related molecules. Descriptors are designed for two complex ...
I joined Stanford in Oct 2012 as the Director of Bioinformatics at Stanford Center for Genomics and Personalized Medicine (SCGPM). My responsibility at the Center was to develop and lead the bioinformatics team and establish a genomics data analysis facility. Currently, SCGPM bioinformatics team is comprised of a dozen scientists and software engineers. The team has a wide range of skill sets including omics, computational biology, machine learning, software engineering, data management, Databases, Visualization, High Performance Computing, IT, and Cloud DevOps. The team is currently supporting several large scale research and clinical programs at Stanford including prestigious consortium efforts and inter-disciplinary collaborations. The team also supports Genetics Bioinformatics Service Center (2013-), a facility that provides best-in-class high performance computational systems, scalable Cloud computing and cutting edge bioinformatics services for the Stanford community. ...
ETHealthworld.com brings latest plos computational biology news, views and updates from all top sources for the Indian Health industry.
Global computational biology market reach a valuation of US$2.9 bn by 2018, rising rapidly from its 2011 valuation of US$0.7 bn, moreover the computational biology market will expand at a 21.30% CAGR worldwide
This course will teach you the basics of how to perform Bulk RNA-Seq Analysis on NIDAP. The course consists of recorded lectures and video tutorials, with a live Discussion webinar you will attend after completing the tutorials. Click here for Details & Registration. ...
Study Bioinformatics & Computational Biology focus on development and application of computational and mathematical models using high-throughput genomic and proteomic data
The splicing mechanism, the process of forming mature messenger RNA (mRNA) by only concatenating exons and removing introns, is an essential step in gene expression. It allows a single gene to have multiple RNA isoforms which potentially code different proteins. In addition, aberrant transcripts generated from non-canonical splicing events (e.g. gene fusions) are believed to be potential drivers in many tumor types and human diseases. Thus, identification and quantification of expressed RNAs from RNA-Seq data become fundamental steps in many clinical studies. For that reason, number of methods have been developed. Most popular computational methods designed for these high-throughput omics data start by analyzing the datasets based on existing gene annotations. However, these tools (i) do not detect novel RNA isoforms and low abundance transcripts; (ii) do not incorporate multi-mapping reads in their read counting strategies in quantifications; (iii) are sensitive to sequencing artifacts. In this ...