AIMC Topic: Sequence Analysis, Protein

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PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

Journal of theoretical biology Feb 1, 2018
Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been s...
Databases, Protein Catalysis Protein Conformation Sequence Analysis, Protein Machine Learning Software
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Prediction of GPCR-Ligand Binding Using Machine Learning Algorithms.

Computational and mathematical methods in medicine Jan 30, 2018
We propose a novel method that predicts binding of G-protein coupled receptors (GPCRs) and ligands. The proposed method uses hub and cycle structures of ligands and amino acid motif sequences of GPCRs, rather than the 3D structure of a receptor or si...
Humans Machine Learning Quercetin ROC Curve Software Binding Sites Ligands Protein Binding False Positive Reactions Algorithms Amino Acid Motifs Receptors, G-Protein-Coupled Reproducibility of Results Sequence Analysis, Protein Area Under Curve
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iMem-2LSAAC: A two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into chou's pseudo amino acid composition.

Journal of theoretical biology Jan 11, 2018
Membrane proteins execute significant roles in cellular processes of living organisms, ranging from cell signaling to cell adhesion. As a major part of a cell, the identification of membrane proteins and their functional types become a challenging jo...
Membrane Proteins Support Vector Machine Sequence Analysis, Protein Neural Networks, Computer Databases, Protein Algorithms Amino Acid Sequence Reproducibility of Results Computational Biology
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ProtDet-CCH: Protein Remote Homology Detection by Combining Long Short-Term Memory and Ranking Methods.

IEEE/ACM transactions on computational biology and bioinformatics Jan 5, 2018
As one of the most challenging tasks in sequence analysis, protein remote homology detection has been extensively studied. Methods based on discriminative models and ranking approaches have achieved the state-of-the-art performance, and these two kin...
Databases, Factual Reproducibility of Results Computational Biology Support Vector Machine Neural Networks, Computer Software Algorithms Amino Acid Motifs Sequence Analysis, Protein Proteins Databases, Protein Sequence Homology, Amino Acid Humans
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Protein structure modeling and refinement by global optimization in CASP12.

Proteins Dec 5, 2017
For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequ...
Molecular Dynamics Simulation Crystallography, X-Ray Protein Conformation Support Vector Machine Protein Folding Humans Sequence Analysis, Protein Models, Statistical Protein Interaction Domains and Motifs Proteins Models, Molecular Machine Learning Algorithms Computational Biology
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Assessment of the model refinement category in CASP12.

Proteins Nov 29, 2017
We here report on the assessment of the model refinement predictions submitted to the 12th Experiment on the Critical Assessment of Protein Structure Prediction (CASP12). This is the fifth refinement experiment since CASP8 (2008) and, as with the pre...
Proteins Models, Molecular Crystallography, X-Ray Humans Protein Conformation Machine Learning Protein Folding Algorithms Sequence Analysis, Protein Computational Biology
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Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants.

Proteins Nov 29, 2017
Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and a database of GO term predic...
Sequence Analysis, Protein PTEN Phosphohydrolase Databases, Protein Models, Biological Machine Learning Humans Gene Ontology Animals Transcriptome Proteomics
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Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

Amino acids Nov 18, 2017
Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithm...
Models, Theoretical Databases, Protein Receptors, G-Protein-Coupled Neural Networks, Computer Amino Acid Sequence Sequence Alignment Machine Learning Sequence Analysis, Protein Algorithms Reproducibility of Results
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Template-based and free modeling of I-TASSER and QUARK pipelines using predicted contact maps in CASP12.

Proteins Nov 14, 2017
We develop two complementary pipelines, "Zhang-Server" and "QUARK", based on I-TASSER and QUARK pipelines for template-based modeling (TBM) and free modeling (FM), and test them in the CASP12 experiment. The combination of I-TASSER and QUARK successf...
Algorithms Protein Folding Computational Biology Sequence Alignment Humans Proteins Machine Learning Databases, Protein Models, Molecular Crystallography, X-Ray Protein Conformation Sequence Analysis, Protein
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Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

Proteins Oct 31, 2017
In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on co...
Datasets as Topic Computational Biology Protein Folding Humans Crystallography, X-Ray Proteins Sequence Alignment Machine Learning Protein Conformation Sequence Analysis, Protein Databases, Protein Algorithms Models, Molecular
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