Datasets protein structure secondary. Medical search. Frequent questions

While high-throughput experimental methods like the yeast two-hybrid (Y2H) method and mass spectrometry are available to discern the function of proteins, the datasets generated by these methods tend to be incomplete and generate false positives [ 9 ]. (biomedcentral.com)
therefore, computational approaches combined with high-throughput experimental datasets are required to identify the function of proteins [ 9 , 14 ]. (biomedcentral.com)
We present diffBUM-HMM, a noise-aware model that enables accurate detection of RNA flexibility and conformational changes from high-throughput RNA structure-probing data. (biomedcentral.com)
Course covers advanced concepts of genomics, molecular biology, and systems biology and explores computational methods for analyzing their high-throughput datasets. (iu.edu)

It was on that occasion that in a conversation with David Moss, Professor of Biomolecular Structures, and his co-worker Dr. Clare Sansom, the idea was conceived to organize the postgraduate course in bioinformatics, this newly emerging interdisciplinary research area as the interface between biological and computational sciences, primarily aimed at research students from Central and Eastern Europe. (iospress.nl)
His research spans a wide range, from the quantum chemistry of small molecules and the spectroscopic properties of proteins, to the application of state-of-the-art statistical and computer science methodology to problems in bioinformatics, drug design and sustainable chemistry. (nottingham.ac.uk)
He is teaching courses on bioinformatics, protein structure and function, protein interactions: computational techniques, big data analysis and handling computational biology lab. (nptel.ac.in)
His main research interests are structural analysis, prediction, folding and stability of globular and membrane proteins, protein interactions and development of bioinformatics databases and tools. (nptel.ac.in)
He has published over 200 research articles, 40 reviews, 5 editorials and a book on Protein Bioinformatics: From Sequence to Function by Elsevier/Academic Press. (nptel.ac.in)
As a consequence, the last few years have seen an increase in the development of a number of bioinformatics tools to detect differentially reactive nucleotides (DRNs) in RNA structure probing datasets. (biomedcentral.com)
Examine application of these techniques to current bioinformatics problems including: genome annotation and comparison, gene finding, RNA secondary structure prediction, protein structure prediction, gene expression analysis, proteomics, and integrative functional genomics. (iu.edu)

We would like to extend the ssHMM software developed by David Heller, a previous member of the lab, to other RNA Binding Protein (RBP) dataset and search for sequence-structure motif hits in uncharacterized RNA sequences. (mpg.de)
Using a single integrated model, NetSurfP-2.0 predicts solvent accessibility, secondary structure, structural disorder, and backbone dihedral angles for each residue of the input sequences. (ku.dk)
However, there are still challenges in accurately predicting protein contact distance when there are few homologous sequences, folding proteins from noisy contact distances, and ranking models of hard targets. (nsf.gov)
Accuracy of prediction performance has been recently improved due to the rapid expansion of protein sequences and the design of libraries in deep learning techniques. (ijitee.org)
I also examined the substrate specificities of more than 200 human protein kinases with peptide microarrays populated with semi-optimal substrate sequences. (dissertation.com)
In the current work, we evaluate the statistical free energy of various secondary structure motifs, including base-pair stacks, hairpin loops, and internal loops, using their statistical frequency obtained from the comparative analysis of more than 50,000 RNA sequences stored in the RNA Comparative Analysis Database (rCAD) at the Comparative RNA Web (CRW) Site. (tmu.edu.tw)
alignment - A comparison of two or more gene or protein sequences in order to determine their degree of similarity in amino acid or bases, respectively. (rcsb.org)
Evolutionary analysis of DNA and protein sequences is typically performed by either assuming that all evolutionary lineages change at the same rate or by avoiding any attempt to directly consider the fact that the rate of evolution changes over time. (lifeboat.com)
This entailed mining available transcriptomic and/or genomic sequence datasets for the presence of homologues of known TIMPs, predicting secondary structures of defined protein sequences, systematic phylogenetic analyses and assessment of differential expression of genes encoding putative TIMPs in the developmental stages of A. suum , N. americanus and Schistosoma haematobium which infect the mammalian hosts. (biomedcentral.com)
A total of 15 protein sequences with high homology to known eukaryotic TIMPs were predicted from the complement of sequence data available for parasitic helminths and subjected to in-depth bioinformatic analyses. (biomedcentral.com)

An intuitive method is used to quantify which features are most important for correct prediction.The resulting well-trained classifier, hotspotter, can robustly predict the small subset of amino acid residues on the surface of a protein that are energetically most important for binding a protein partner: the interaction hot spots. (pubpharm.de)
Application to the ACE2 (angiotensin converting enzyme 2) receptor, which mediates COVID-19 virus entry into human cells, identified the critical hot spot triad of ACE2 residues at the center of the small interface with the CoV-2 spike protein. (pubpharm.de)
Proteins are large biomolecules, or macromolecules, consisting of one or more long chains of amino acid residues. (deeplearningindaba.com)
The contents of scount.xvg are the number of residues present in each type of secondary structure, and you know the total number of residues. (mail-archive.com)

In our previous work, we developed a six-point classification scoring schema with annotation pertaining to protein family scores, orthology, protein interaction/association studies, bidirectional best BLAST hits, sorting signals, known databases and visualizers which were used to validate protein interactions. (biomedcentral.com)
Another aspect of Hirst's research focuses on the study of protein-ligand interactions, using techniques including QSAR, machine learning, neural networks, docking, molecular dynamics (MD) simulations and quantum chemistry. (nottingham.ac.uk)
Developing accurate and efficient coarse-grained representations of proteins is crucial for understanding their folding, function, and interactions over extended time scales. (bvsalud.org)
Owing to its theoretical transferability and ability to use solely experimental static structures as training data, we anticipate that this approach will prove advantageous for developing new protein force fields and further advancing the study of protein dynamics, folding, and interactions. (bvsalud.org)
The second section will be devoted to applications such as prediction of protein structure, folding rates, stability upon mutation, and intermolecular interactions. (nptel.ac.in)
Protein interactions enable much more complex behavior than the sum of the individual protein parts would suggest and represents a level of biological complexity requiring full understanding when unravelling cellular processes. (uu.nl)
Allostery - This is a type of effect seen in proteins where the binding of a molecule, ion etc. to one location can have an impact of the structure and interactions at another location. (rcsb.org)
Our ~2.7 Å structure of alcohol dehydrogenase (82 kDa) proves that bound ligands can be resolved with high fidelity to enable investigation of drug-target interactions. (nature.com)
A detailed understanding of the molecular biology of parasitic helminths, and in particular of the structure and function of key genes and gene products playing essential roles in host-parasite interactions, could provide a basis for the design of novel therapeutics. (biomedcentral.com)
rium properties, completely determined by the interactions within crystal structures of 38 nonhomologous proteins, we find that it the system. (lu.se)
The student will learn how spectroscopy and models for intermolecular interactions can be used to understand basic properties of biomolecules such as proteins, DNA and membranes. (lu.se)

By conducting molecular dynamics (MD) simulations on various protein-ligand complexes and metadynamics (MTD) simulations on a ligand, we showcase the capabilities of our implementation of NNP/MM. It has enabled us to increase the simulation speed by â ¼5 times and achieve a combined sampling of 1 µs for each complex, marking the longest simulations ever reported for this class of simulations. (bvsalud.org)

She has used code-breaking strategies to predict protein structures and applied computational techniques to drug discovery. (technologyreview.com)
The ability to predict local structural features of a protein from the primary sequence is of paramount importance for unraveling its function in absence of experimental structural information. (ku.dk)
In this research proposed a deep recurring network unit method called stacked bidirectional long-term memory (Stacked BLSTM) units to predict 3-class protein secondary structure from protein sequence information using a bidirectional LSTM layer. (ijitee.org)
The model is applied to predict the secondary structure content (per-residue level and overall content), protein solubility, and sequencing tasks. (aip.org)

The inter- and intramolecular forces between this RNA and other small molecules and macromolecules, in addition to other factors in the cell such as pH, ionic strength, and temperature, influence the complex dynamics associated with transition of a single stranded RNA to its secondary and tertiary structure. (tmu.edu.tw)
Determining high-resolution structures of biological macromolecules amassing less than 100 kilodaltons (kDa) has been a longstanding goal of the cryo-electron microscopy (cryo-EM) community. (nature.com)
To cause sensitization, a chemical must bind to macromolecules (proteins) in the skin. (cdc.gov)

active site - A region in proteins and nucleic acids (that participate in chemical reactions), where reacting molecules (substrates) bind and make specific contacts necessary for chemical catalysis. (rcsb.org)
Proteins perform a vast array of functions within organisms, including catalysing metabolic reactions, DNA replication, responding to stimuli, providing structure to cells, and organisms, and transporting molecules from one location to another. (deeplearningindaba.com)
On aver- comprising some 1015 protein molecules. (lu.se)
Since the structural features of RNA are of major importance to their biological function, there is much interest in predicting RNA structure, either in free form or in interaction with various ligands, including proteins, metabolites and other molecules. (nyu.edu)
Fig. 4: Arrangement of protein subunits and lipid molecules in the inner-membrane complex. (nature.com)

This advanced course covers how massive clinical and biomedical genomic sequencing datasets from various sequencing platforms motivate computational needs and tasks for analysis, how to devise approaches for analyzing these datasets, how to develop sound hypotheses and predictions from them, and related ethical, privacy, and legal issues. (iu.edu)

In this chapter, we address these issues while developing and sharing protocols to build a robust dataset and rigorously compare several predictive classifiers using the open-source Python machine learning library, scikit-learn. (pubpharm.de)
The resultant data were used to expand the training datasets for development of next generation protein kinase substrate predictive algorithms. (dissertation.com)
This dataset is related to classification and predictive tasks. (webstek.org)

I am working on a project to classify lung CT images (cancer/non-cancer) using CNN model, for that I need free dataset with annotation file. (webstek.org)
It surveys a wide range of topics including computational sequence analysis, sequence homology searching and motif finding, gene finding and genome annotation, protein structure analysis and modeling, genomics and SNP analysis, DNA microarrays and gene expression analysis, Proteomics, network/systems biology, and biological knowledge discovery. (iu.edu)

We observe a correlation of 80% between predictions and experimental data for solvent accessibility, and a precision of 85% on secondary structure 3-class predictions. (ku.dk)
AbstractComputational methods that produce accurate protein structure models from limited experimental data, e.g. from nuclear magnetic resonance (NMR) spectroscopy, hold great potential for biomedical research. (sciencegate.app)
Proteins that are predicted to be expressed from an open reading frame, but for which there is no experimental evidence of translation are known as hypothetical proteins (HPs). (biomedcentral.com)
However, Experimental PSS approaches are time consuming and difficult to implement, and its most essential to establish effective computing methods for predicting on protein sequence structure. (ijitee.org)
Furthermore, we show that a single coarse-grained potential can integrate all twelve proteins and can capture experimental structural features of mutated proteins. (bvsalud.org)
Multiple high-quality models (experimental and theoretical) of all possible Leishmania proteins, both in apo (unboud) and holo (bound with a small molecule) form, with annotated known binding pockets and a way to translate these models to reflect particular species of the pathogen. (deeplearningindaba.com)
most predictions have very large root mean square deviations from the experimental structure. (nyu.edu)

Across the whole genome, approximately 2% of the genes code for proteins, while the remaining are non-coding or still functionally unknown [ 1 ]. (biomedcentral.com)
The genome atlases allowed for distinguishing distinct DNA structures and highlighted suspicious high transcription zones. (mdpi.com)

Amino Acid Sequence, Protein Secondary Structure, Deep Bidirectional LSTM. (ijitee.org)
A variant classifier was trained and validated for proteins where only the amino acid sequence is available, augmented by secondary structure assignment. (pubpharm.de)

One such widely used technique is protein-protein interaction (PPI) analyses, which is considered valuable in interpreting the function of HPs [ 6 ]. (biomedcentral.com)
Our analyses of datasets generated with a variety of RNA probing chemistries demonstrate the value of diffBUM-HMM for quantitatively detecting RNA structural changes and RNA-binding protein binding sites. (biomedcentral.com)

Comparisons of primary, secondary and tertiary structures supported the hypothesis that protein kinases and choline kinases evolved from an ancient aminoacyl-tRNA ligase. (dissertation.com)
In recent years, an increasing number of researchers have developed novel RNA algorithms for predicting RNA secondary and tertiary structures. (nyu.edu)

Different computational methods have been designed for estimating protein function based on the information generated from sequence similarity, subcellular localization, phylogenetic profiles, mRNA expression profiles, homology modelling etc. [ 15 ]. (biomedcentral.com)
The influence of dataset homology and a rigorous evaluation strategy on protein secondary structure prediction. (nctu.edu.tw)

Examples of this kind of meta data are secondary structures (RNA and protein), protein hydrophobicity assignments, or other alternative alphabets for polypeptides, sequence quality data and nucleotide alignments with translations. (metacpan.org)

The accurate prediction of the secondary and tertiary structure of an RNA with different folding algorithms is dependent on several factors, including the energy functions. (tmu.edu.tw)
Problems in biology and biomedicine will motivate the development of algorithms to apply to these datasets. (iu.edu)
To evaluate the performance of the most recent RNA 3D folding algorithms, we provide a comparative study in order to test the performance of available 3D structure prediction algorithms for an RNA data set of 43 structures of various lengths and motifs. (nyu.edu)

Therefore, characterizing the uncharacterized proteins helps to understand the biological architecture of the cell [ 8 ]. (biomedcentral.com)
A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. (bvsalud.org)
a With machine learning now transforming the sciences, successful prediction of biological structure or activity is mainly limited by the extent and quality of data available for training, the astute choice of features for prediction, and thorough assessment of the robustness of prediction on a variety of new cases. (pubpharm.de)
proteins could carry out their biological functions. (lu.se)
Topics include programming for the web, depiction of chemical and biological structures in 2D and 3D, science informatics tool kits, software APIS, AI and machine-learning algorithm development, high-performance computing, database management, managing a small software development group, and design and usability of science informatics software. (iu.edu)

Statistical energy was computed from the structural statistics for several datasets. (tmu.edu.tw)
He does this by developing statistical techniques for analyzing DNA and protein sequence data. (lifeboat.com)

Cysteine-Selective Modification of Peptides and Proteins via Desulfurative C-C Bond Formation CHEMISTRY-A EUROPEAN JOURNAL. (nottingham.ac.uk)
There are 20 different alpha amino acids commonly found in nature that can covalently link with each other to form short peptides or longer proteins. (rcsb.org)
Brain natriuretic peptide (BNP) is a member of a family of four human natriuretic peptides that share a common 17-peptide ring structure. (medscape.com)

We obtained metagenomic datasets used for bioinformatic screening from OxBRC Prospective Cohort Study in Hepatitis C (ethics reference 09/H0604/20), the Short Pulse Antiretroviral Therapy at seroConversion cohort ( 11 ), Thames Valley HIV Cohort Study ( 12 ), and a cohort in the Democratic Republic of the Congo (DRC) ( 13 ). (cdc.gov)

The computational experiment collects tests and to hold performance analysis and analysis of dependency for the algorithm quality and structure parameters. (machinelearning.ru)
Chi-Chun Chen, Yu-Wei Huang, Hsuan-Cheng Huang, Wei-Cheng Lo *, Ping-Chiang Lyu* (2022, Nov). SeqCP: A sequence-based algorithm for searching circularly permuted proteins. (nctu.edu.tw)

Abstract Motivation Deep learning has become the dominant technology for protein contact prediction. (nsf.gov)

We used the dataset of experimentally validated human miRNA hairpins from miRBase, and extracted fourteen nucleotides around Dicer cleavage sites. (biomedcentral.com)
Since all of the factors that affect the formation of an RNAs 3D structure cannot be determined experimentally, statistically derived potential energy has been used in the prediction of protein structure. (tmu.edu.tw)

These results indicate that machine learning coarse-grained potentials could provide a feasible approach to simulate and understand protein dynamics. (bvsalud.org)

Knowledge of the secondary structure and solvent accessibility of a protein plays a vital role in the prediction of fold, and eventually the tertiary structure of the protein. (edu.au)

Our methodology involves simulating proteins with molecular dynamics and utilizing the resulting trajectories to train a neural network potential through differentiable trajectory reweighting. (bvsalud.org)
Once trained, the model can be employed to run parallel molecular dynamics simulations and sample folding events for proteins both within and beyond the training distribution, showcasing its extrapolation capabilities. (bvsalud.org)
For training, we build a unique dataset of unbiased all-atom molecular dynamics simulations of approximately 9 ms for twelve different proteins with multiple secondary structure arrangements. (bvsalud.org)
Mrozek D, Mastej A, Malysiak B: Protein Molecular Viewer for Visualizing Structures Stored in the PDBML Format. (bioclipse.net)
You can use the structure of the protein to see if your newly found molecule fits well into the pocket (molecular docking). (deeplearningindaba.com)
HM038439), was 731 nucleotides long and encoded a partial protein of 124 amino acids with predicted molecular weight of 13.65 kDa and calculated 10.01 isoelectric point. (scialert.net)

His calculations on protein circular dichroism spectroscopy, a key technique in structural biology, are the most accurate to be published. (nottingham.ac.uk)
Protein Secondary Structure (PSS) is one of most complex problem in biology PSS is important for determining tertiary structure in the future, for studying protein fiction and drug design. (ijitee.org)
Understanding the structure of RNA is key to unravel its in vivo function, and it is also highly relevant to biomedicine, drug discovery, and synthetic biology [ 1 - 4 ]. (biomedcentral.com)

The first residue of the PWWP motif modulates HATH domain binding, stability, and protein-protein interaction. (nctu.edu.tw)

These known-unknown regions for which no functional links are discovered, i.e. those with no biochemical properties or obvious relatives in protein and nucleic acid databases are known as orphan genes, and the end products are called HPs [ 2 ]. (biomedcentral.com)

MicroMass: A dataset to explore machine learning approaches for the identification of microorganisms from mass-spectrometry data. (webstek.org)

Proteins differ from one another primarily in their sequence of amino acids, which is dictated by the nucleotide sequence of their genes, and which usually results in protein folding into a specific 3D structure that determines its activity. (deeplearningindaba.com)

Further trained on inverse tasks, the model is rendered capable of designing proteins with these properties as target features. (aip.org)
We find that adding additional tasks yields emergent synergies that the model exploits in improving overall performance, beyond what would be possible by training a model on each dataset alone. (aip.org)

Viterbi path) and have an idea about RNA secondary structure prediction and/or motif finding. (mpg.de)
alpha helix - A secondary structural motif of a protein. (rcsb.org)

The extensively examined extracellular signal-regulated kinases (ERKs) 1/2 from the mitogen-activated protein kinase family were used as a model in this study. (dissertation.com)
Tissue inhibitors of metalloproteases (TIMPs) are a multifunctional family of proteins that orchestrate extracellular matrix turnover, tissue remodelling and other cellular processes. (biomedcentral.com)

Our experiment points out new directions for QA problem and our method could be widely used for protein structure prediction problem. (sciencegate.app)
The success of MULTICOM system clearly shows that protein contact distance prediction and model selection driven by deep learning holds the key of solving protein structure prediction problem. (nsf.gov)

The other PDB files used for analysis and comparison in this work were downloaded from the RCSB PDB website ( http://www.rcsb.org/ ), including the structures of A. thaliana Toc75 POTRA domains ( 5UAY ), the NMR structure of the C. reinhardtii preFdx1 transit peptide ( 1FCT ) and the crystal structure of RopP2 from Ralstonia solanacearum ( 5W3X ). (nature.com)

Techniques to decipher sequence-structure-function relationship, especially in terms of functional modelling of the HPs have been developed by researchers, but using the features as classifiers for HPs has not been attempted. (biomedcentral.com)
While many proteins often interact with other proteins towards expediting their functions, there are challenges that are not just limited to their function but also to their regulation [ 7 ]. (biomedcentral.com)
For any given tool, the impact thresholds defined for the set of variants with the same effect on function as the variant examined, are preferred over those defined for the full dataset. (ithanet.eu)
Richardson, L. G. L. & Schnell, D. J. Origins, function, and regulation of the TOC-TIC general protein import machinery of plastids. (nature.com)
function and secondary structure]] of our protein we will determine the 3D structure as well as how much influence one, or several, SNPs has/have on this structure. (tu-muenchen.de)
One of the hallmarks of type 1 but also type 2 diabetes is pancreatic islet inflammation, associated with altered pancreatic islet function and structure, if unresolved. (lu.se)
C. Peterson, M. Ringne´r / Artificial Intelligence in Medicine 28 (2003) 59-74 structure and function, cellular metabolism, development of cells and tissues, and response of organisms to their environments. (lu.se)

We assessed the accuracy of NetSurfP-2.0 on several independent test datasets and found it to consistently produce state-of-the-art predictions for each of its output features. (ku.dk)
Traditional protein QA methods suffer from searching databases or comparing with other models for making predictions, which usually fail. (sciencegate.app)

It is designed to solve the protein secondary structure recognition problem. (machinelearning.ru)

Any way that data from known structures can creep into your inputs invaliates your testing, and makes it impossible to say with confidence that your method does anything useful. (bio.net)
doi:10.1002/prot.21791 I see a lot of 'prediction' work that is complete garbage, because the authors fooled themselves by using data that could only come from knowing the real structures. (bio.net)
Two main factors affect the utility of potential prediction tools: their accuracy must enable extraction of reliable structural information on the proteins of interest, and their runtime must be low to keep pace with sequencing data being generated at a constantly increasing speed. (ku.dk)
The NMR-assisted modeling challenge in CASP13 provided a blind test to explore the capabilities and limitations of current modeling techniques in leveraging NMR data which had high sparsity, ambiguity and error rate for protein structure prediction. (sciencegate.app)
Remarkably, this method requires only the native conformation of proteins, eliminating the need for labeled data derived from extensive simulations or memory-intensive end-to-end differentiable simulations. (bvsalud.org)
Advances in Cheminformatics Methodologies and Infrastructure to Support the Data Mining of Large, Heterogeneous Chemical Datasets. (bioclipse.net)
You can use the shape of a binding pocket to search for a similar one in the Protein Data Bank. (deeplearningindaba.com)
References and links to large data sets with drug structures and their activities. (deeplearningindaba.com)
Parkinson Speech Dataset with Multiple Types of Sound Recordings: The training data belongs to 20 Parkinson's Disease (PD) patients and 20 healthy subjects. (webstek.org)
84. chipseq: ChIP-seq experiments characterize protein modifications or binding at Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack, 13. (webstek.org)
The primary data, structure factors of Bragg reflections, AMSDs can be predicted solely on the basis of packing density. (lu.se)
The reference of Must, Dallal and Di- ing public or private middle and secondary etz uses the National Health and Nutrition schools in the Nile Delta (in Cairo and Examination Survey (NHANES) I data, nearby rural areas). (who.int)
8]. For children and adolescents, it clas- wait, dietary and blood data were collected sifies overweight as 85th percentile and for 245 secondary school-aged girls along obesity as 95th percentile. (who.int)

Here we report the cryo-electron microscopy structure of the TOC-TIC supercomplex from Chlamydomonas reinhardtii . (nature.com)

Deep learning also successfully integrated one‐dimensional structural features, two‐dimensional contact information, and three‐dimensional structural quality scores to improve protein model quality assessment, where the contact prediction was demonstrated to consistently enhance ranking of protein models for the first time. (nsf.gov)

The major subunits of the TOC complex (Toc75, Toc90 and Toc34) and TIC complex (Tic214, Tic20, Tic100 and Tic56), three chloroplast translocon-associated proteins (Ctap3, Ctap4 and Ctap5) and three newly identified small inner-membrane proteins (Simp1-3) have been located in the supercomplex. (nature.com)
As the largest protein, Tic214 traverses the inner membrane, the intermembrane space and the outer membrane, connecting the TOC complex with the TIC proteins. (nature.com)
Uncovering the protein translocon at the chloroplast inner envelope membrane. (nature.com)

Predicting residue‐residue distance relationships (eg, contacts) has become the key direction to advance protein structure prediction since 2014 CASP11 experiment, while deep learning has revolutionized the technology for contact and distance distribution prediction since its debut in 2012 CASP10 experiment. (nsf.gov)
During 2018 CASP13 experiment, we enhanced our MULTICOM protein structure prediction system with three major components: contact distance prediction based on deep convolutional neural networks, distance‐driven template‐free (ab initio) modeling, and protein model ranking empowered by deep learning and contact prediction. (nsf.gov)
Our experiment demonstrates that contact distance prediction and deep learning methods are the key reasons that MULTICOM was ranked 3rd out of all 98 predictors in both template‐free and template‐based structure modeling in CASP13. (nsf.gov)

However, if MCC equals neither −1, 0, or +1, it is not a reliable indicator of how similar a predictor is to random guessing because MCC is dependent on the dataset. (wikipedia.org)
Albumin measurements are used in the diagnosis and treatment of diseases involving the liver and/or kidneys, and are frequently used to assess nutritional status because plasma levels of albumin are dependent on protein intake. (cdc.gov)

DSSP calculates secondary structure from hydrogen bonds, which will be absent in a CG model. (mail-archive.com)

59. Cervical Cancer Risk Factors for Biopsy: This Dataset is Obtained from UCI Repository and kindly acknowledged! (webstek.org)

These proposed methods are tested on the RS126 and CB513 datasets. (edu.au)
A blind test on the EVA dataset gives an average Q3 accuracy of 74.5% and ranks in top five protein structure prediction methods. (edu.au)
PHENIX (Python-based Hierarchical ENvironment for Integrated Xtallography) is a software suite for the automated determination and refinement of macromolecular structures using X-ray crystallography and other methods. (uni-konstanz.de)
We previously demonstrated that a transmission electron microscope (TEM) operating at 200 keV equipped with a K2 Summit direct electron detector (DED) could be used to resolve a ~150 kDa protein complex to ~2.6 Å using conventional defocus-based SPA methods 12 . (nature.com)

This version of hotspotter requiring fewer features is almost as robust as the structure-based classifier. (pubpharm.de)

QSAR Bioconcentration classes dataset: Dataset of manually-curated Bioconcentration factor (BCF, fish) and mechanistic classes for QSAR modeling. (webstek.org)
This perspective focuses on two areas that have yielded new useful information during the last 20 years: (i) structure-activity relationship (SAR) studies of contact allergy based on the concept of hapten-protein binding and (ii) mechanistic investigations regarding activation of nonsensitizing compounds to contact allergens by air oxidation or skin metabolism. (cdc.gov)

Our intein dataset greatly expands the spectrum of intein-containing proteins and provides insights into the evolution of inteins in eukaryotes. (lu.se)

Motivation: The successful application of deep learning has promoted progress in protein model quality assessment. (sciencegate.app)
How to use model quality assessment to further improve the accuracy of protein structure prediction, especially not reliant on the existing templates, is helpful for unraveling the folding mechanism. (sciencegate.app)
Here, we investigate whether model quality assessment can be introduced into structure prediction to form a closed-loop feedback, and iteratively improve the accuracy of de novo protein structure prediction. (sciencegate.app)

In addition to improved accuracy, the processing time has been optimized to allow predicting more than 1000 proteins in less than 2 hours, and complete proteomes in less than 1 day. (ku.dk)
On the CB513 dataset, sevenfold cross-validation accuracy of 77.9% was obtained using the proposed encoding method. (edu.au)
A simple strategy to enhance the speed of protein secondary structure prediction without sacrificing accuracy. (nctu.edu.tw)

The backbone atoms of the peptide in this region forms a right handed helical structure, hence the name. (rcsb.org)
Brain natriuretic peptide (BNP) is a protein secreted by the ventricular musculature in response to volume or pressure overload. (medscape.com)

2003. " Manifold: Protein Fold Recognition Based On Secondary Structure, Sequence Similarity And Enzyme Classification " . (uni-heidelberg.de)
22. Amphibians: The dataset is a multilabel classification problem. (webstek.org)

NetSurfP-2.0 is sequence-based and uses an architecture composed of convolutional and long short-term memory neural networks trained on solved protein structures. (ku.dk)
We report a flexible language-model-based deep learning strategy, applied here to solve complex forward and inverse problems in protein modeling, based on an attention neural network that integrates transformer and graph convolutional architectures in a causal multi-headed graph mechanism, to realize a generative pretrained model. (aip.org)

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