AIMC Topic: Binding Sites

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Machine learning reveals a non-canonical mode of peptide binding to MHC class II molecules.

Immunology Jun 19, 2017
MHC class II molecules play a fundamental role in the cellular immune system: they load short peptide fragments derived from extracellular proteins and present them on the cell surface. It is currently thought that the peptide binds lying more or les...
Protein Binding Computational Biology Databases, Protein Antibodies, Monoclonal Neural Networks, Computer Machine Learning Peptides Ligands Binding Sites Protein Interaction Domains and Motifs Histocompatibility Antigens Class II Structure-Activity Relationship Mutation Epitopes Humans
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Editorial-Sequences and topology.

Current opinion in structural biology Jun 4, 2017
Humans Machine Learning Thermodynamics Protein Interaction Mapping Protein Multimerization Animals Protein Conformation, beta-Strand Molecular Docking Simulation Protein Interaction Domains and Motifs Protein Binding Computational Biology Protein Conformation, alpha-Helical Proteins Binding Sites
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TIGERi: modeling and visualizing the responses to perturbation of a transcription factor network.

BMC bioinformatics May 31, 2017
BACKGROUND: Transcription factor (TF) networks play a key role in controlling the transfer of genetic information from gene to mRNA. Much progress has been made on understanding and reverse-engineering TF network topologies using a range of experimen...
Binding Sites Mitogen-Activated Protein Kinase 14 Mice Transcription Factors Mice, Knockout Machine Learning Animals Transcriptome Gene Regulatory Networks
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pDHS-SVM: A prediction method for plant DNase I hypersensitive sites based on support vector machine.

Journal of theoretical biology May 26, 2017
DNase I hypersensitive sites (DHSs) are accessible chromatin regions hypersensitive to cleavages by DNase I endonucleases. DHSs are indicative of cis-regulatory DNA elements (CREs), all of which play important roles in global gene expression regulati...
Dinucleotide Repeats Arabidopsis Regulatory Sequences, Nucleic Acid Deoxyribonuclease I Algorithms Binding Sites Genome, Plant Support Vector Machine Oryza
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Protein-Protein Interaction Interface Residue Pair Prediction Based on Deep Learning Architecture.

IEEE/ACM transactions on computational biology and bioinformatics May 19, 2017
MOTIVATION: Proteins usually fulfill their biological functions by interacting with other proteins. Although some methods have been developed to predict the binding sites of a monomer protein, these are not sufficient for prediction of the interactio...
Molecular Docking Simulation Deep Learning Protein Binding Protein Conformation Binding Sites Computational Biology Proteins Surface Properties
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Discriminating between HuR and TTP binding sites using the k-spectrum kernel method.

PloS one Mar 23, 2017
BACKGROUND: The RNA binding proteins (RBPs) human antigen R (HuR) and Tristetraprolin (TTP) are known to exhibit competitive binding but have opposing effects on the bound messenger RNA (mRNA). How cells discriminate between the two proteins is an in...
Tristetraprolin Catalytic Domain Humans Binding Sites Models, Theoretical ELAV-Like Protein 1 Support Vector Machine
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Staged heterogeneity learning to identify conformational B-cell epitopes from antigen sequences.

BMC genomics Mar 14, 2017
BACKGROUND: The broad heterogeneity of antigen-antibody interactions brings tremendous challenges to the design of a widely applicable learning algorithm to identify conformational B-cell epitopes. Besides the intrinsic heterogeneity introduced by di...
B-Lymphocytes Supervised Machine Learning Antigens Humans Protein Conformation, alpha-Helical Protein Interaction Domains and Motifs Protein Binding Epitopes, B-Lymphocyte Protein Conformation, beta-Strand Binding Sites Models, Statistical Epitope Mapping Antigen-Antibody Complex
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Active learning for computational chemogenomics.

Future medicinal chemistry Mar 6, 2017
AIM: Computational chemogenomics models the compound-protein interaction space, typically for drug discovery, where existing methods predominantly either incorporate increasing numbers of bioactivity samples or focus on specific subfamilies of protei...
Computational Biology Proteins Models, Chemical Machine Learning Binding Sites Drug Discovery Computer Simulation Genomics Ligands Databases, Chemical
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RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

BMC bioinformatics Feb 28, 2017
BACKGROUND: RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recog...
Nucleotide Motifs Neural Networks, Computer RNA-Binding Proteins Machine Learning Data Mining Algorithms Sequence Analysis, RNA RNA Protein Binding Binding Sites
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Imputation for transcription factor binding predictions based on deep learning.

PLoS computational biology Feb 24, 2017
Understanding the cell-specific binding patterns of transcription factors (TFs) is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard....
Binding Sites Protein Interaction Mapping Chromatin Immunoprecipitation Humans Neural Networks, Computer Machine Learning Transcription Factors Reproducibility of Results High-Throughput Nucleotide Sequencing Hep G2 Cells Sensitivity and Specificity K562 Cells Protein Binding
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