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Binding Sites

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ACME: pan-specific peptide-MHC class I binding prediction through attention-based deep neural networks.

Bioinformatics (Oxford, England) Dec 1, 2019
MOTIVATION: Prediction of peptide binding to the major histocompatibility complex (MHC) plays a vital role in the development of therapeutic vaccines for the treatment of cancer. Algorithms with improved correlations between predicted and actual bind...
Computational Biology Histocompatibility Antigens Class I Attention Binding Sites Neural Networks, Computer Algorithms Peptides Protein Binding
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Neural networks with circular filters enable data efficient inference of sequence motifs.

Bioinformatics (Oxford, England) Oct 15, 2019
MOTIVATION: Nucleic acids and proteins often have localized sequence motifs that enable highly specific interactions. Due to the biological relevance of sequence motifs, numerous inference methods have been developed. Recently, convolutional neural n...
Protein Binding Proteins DNA Binding Sites Neural Networks, Computer
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Min3: Predict microRNA target gene using an improved binding-site representation method and support vector machine.

Journal of bioinformatics and computational biology Oct 1, 2019
MicroRNAs are single-stranded noncoding RNAs known to down-regulate target genes at the protein or mRNA level. Computational prediction of targets is essential for elucidating the detailed functions of microRNA. However, prediction specificity and se...
Gene Knockout Techniques 3' Untranslated Regions Models, Genetic Humans MicroRNAs Support Vector Machine Software HeLa Cells Databases, Genetic Computational Biology Gene Knockdown Techniques Binding Sites RNA, Messenger
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Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework.

Nucleic acids research Sep 5, 2019
The identification of transcription factor binding sites and cis-regulatory motifs is a frontier whereupon the rules governing protein-DNA binding are being revealed. Here, we developed a new method (DEep Sequence and Shape mOtif or DESSO) for cis-re...
Computational Biology Transcription Factors DNA Gene Expression Regulation Humans Deep Learning Protein Binding K562 Cells Binding Sites Nucleotide Motifs
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The PSIPRED Protein Analysis Workbench: 20 years on.

Nucleic acids research Jul 2, 2019
The PSIPRED Workbench is a web server offering a range of predictive methods to the bioscience community for 20 years. Here, we present the work we have completed to update the PSIPRED Protein Analysis Workbench and make it ready for the next 20 year...
Internet Amino Acid Sequence History, 21st Century Molecular Sequence Annotation Gene Ontology Binding Sites Sequence Alignment Software Protein Binding Proteins Models, Molecular Protein Conformation, beta-Strand Sequence Homology, Amino Acid Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical
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mCSM-PPI2: predicting the effects of mutations on protein-protein interactions.

Nucleic acids research Jul 2, 2019
Protein-protein Interactions are involved in most fundamental biological processes, with disease causing mutations enriched at their interfaces. Here we present mCSM-PPI2, a novel machine learning computational tool designed to more accurately predic...
Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Thermodynamics Mutation, Missense Protein Interaction Mapping Protein Binding Humans Proteins Machine Learning Internet Software Benchmarking Datasets as Topic Crystallography, X-Ray Binding Sites
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PrankWeb: a web server for ligand binding site prediction and visualization.

Nucleic acids research Jul 2, 2019
PrankWeb is an online resource providing an interface to P2Rank, a state-of-the-art method for ligand binding site prediction. P2Rank is a template-free machine learning method based on the prediction of local chemical neighborhood ligandability cent...
Thermodynamics Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Ligands Datasets as Topic Binding Sites Machine Learning Software Protein Binding Proteins Internet Benchmarking Amino Acid Sequence Humans
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AIControl: replacing matched control experiments with machine learning improves ChIP-seq peak identification.

Nucleic acids research Jun 4, 2019
ChIP-seq is a technique to determine binding locations of transcription factors, which remains a central challenge in molecular biology. Current practice is to use a 'control' dataset to remove background signals from a immunoprecipitation (IP) 'targ...
High-Throughput Nucleotide Sequencing Binding Sites Chromatin Immunoprecipitation Protein Binding Humans Computational Biology Machine Learning Transcription Factors Algorithms Sequence Analysis, DNA Reproducibility of Results
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Identifying short disorder-to-order binding regions in disordered proteins with a deep convolutional neural network method.

Journal of bioinformatics and computational biology Feb 1, 2019
Molecular recognition features (MoRFs) are key functional regions of intrinsically disordered proteins (IDPs), which play important roles in the molecular interaction network of cells and are implicated in many serious human diseases. Identifying MoR...
Amino Acid Sequence Intrinsically Disordered Proteins Binding Sites Protein Binding Computational Biology Humans Membrane Proteins Neural Networks, Computer Databases, Protein Deep Learning
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Using two-dimensional convolutional neural networks for identifying GTP binding sites in Rab proteins.

Journal of bioinformatics and computational biology Feb 1, 2019
Deep learning has been increasingly and widely used to solve numerous problems in various fields with state-of-the-art performance. It can also be applied in bioinformatics to reduce the requirement for feature extraction and reach high performance. ...
Binding Sites rab GTP-Binding Proteins Guanosine Triphosphate Databases, Protein Humans Amino Acids Neural Networks, Computer Amino Acid Sequence Deep Learning Computational Biology
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