AIMC Topic: Proteins

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LoopIng: a template-based tool for predicting the structure of protein loops.

Bioinformatics (Oxford, England) Aug 6, 2015
MOTIVATION: Predicting the structure of protein loops is very challenging, mainly because they are not necessarily subject to strong evolutionary pressure. This implies that, unlike the rest of the protein, standard homology modeling techniques are n...
Databases, Protein Models, Molecular Protein Conformation Machine Learning Software Proteins
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Machine Learnable Fold Space Representation based on Residue Cluster Classes.

Computational biology and chemistry Jul 30, 2015
MOTIVATION: Protein fold space is a conceptual framework where all possible protein folds exist and ideas about protein structure, function and evolution may be analyzed. Classification of protein folds in this space is commonly achieved by using sim...
Cluster Analysis Machine Learning Proteins Protein Folding
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idDock+: Integrating Machine Learning in Probabilistic Search for Protein-Protein Docking.

Journal of computational biology : a journal of computational molecular cell biology Jul 29, 2015
Predicting the three-dimensional native structures of protein dimers, a problem known as protein-protein docking, is key to understanding molecular interactions. Docking is a computationally challenging problem due to the diversity of interactions an...
Binding Sites Protein Multimerization Proteins Ligands Protein Conformation Protein Binding Computational Biology Machine Learning Algorithms Molecular Docking Simulation
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Using distant supervised learning to identify protein subcellular localizations from full-text scientific articles.

Journal of biomedical informatics Jul 26, 2015
Databases of curated biomedical knowledge, such as the protein-locations reflected in the UniProtKB database, provide an accurate and useful resource to researchers and decision makers. Our goal is to augment the manual efforts currently used to cura...
Knowledge Bases Data Curation Proteins Databases, Protein Supervised Machine Learning
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A novel method based on physicochemical properties of amino acids and one class classification algorithm for disease gene identification.

Journal of biomedical informatics Jul 2, 2015
Identifying the genes that cause disease is one of the most challenging issues to establish the diagnosis and treatment quickly. Several interesting methods have been introduced for disease gene identification for a decade. In general, the main diffe...
Humans Artificial Intelligence Algorithms Computational Biology Support Vector Machine Parkinson Disease Reproducibility of Results Diagnosis, Computer-Assisted ROC Curve Probability False Positive Reactions Principal Component Analysis Regression Analysis Amino Acids Proteins Amino Acid Sequence
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Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins.

Cell reports Jul 2, 2015
Alternative splicing acts on transcripts from almost all human multi-exon genes. Notwithstanding its ubiquity, fundamental ramifications of splicing on protein expression remain unresolved. The number and identity of spliced transcripts that form sta...
Protein Structure, Tertiary Exons Alternative Splicing Supervised Machine Learning Humans Protein Isoforms ROC Curve Proteins Area Under Curve
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Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.

Scientific reports Jun 22, 2015
Direct prediction of protein structure from sequence is a challenging problem. An effective approach is to break it up into independent sub-problems. These sub-problems such as prediction of protein secondary structure can then be solved independentl...
Machine Learning Solvents Protein Structure, Secondary Models, Molecular Amino Acids Algorithms Proteins Databases, Protein
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PaPI: pseudo amino acid composition to score human protein-coding variants.

BMC bioinformatics Apr 19, 2015
BACKGROUND: High throughput sequencing technologies are able to identify the whole genomic variation of an individual. Gene-targeted and whole-exome experiments are mainly focused on coding sequence variants related to a single or multiple nucleotide...
Algorithms Proteins Amino Acids Artificial Intelligence Software Exome Humans Genetic Variation High-Throughput Nucleotide Sequencing Genome, Human
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Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

BMC bioinformatics Apr 17, 2015
BACKGROUND: Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when boun...
Protein Binding Ligands Software Humans Proteins Drug Design Binding Sites Artificial Intelligence Drug Discovery
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Woods: A fast and accurate functional annotator and classifier of genomic and metagenomic sequences.

Genomics Apr 8, 2015
Functional annotation of the gigantic metagenomic data is one of the major time-consuming and computationally demanding tasks, which is currently a bottleneck for the efficient analysis. The commonly used homology-based methods to functionally annota...
Sequence Analysis, Protein Proteins Metagenomics Molecular Sequence Annotation Humans Machine Learning Software Genomics
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