AIMC Topic: Binding Sites

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BionoiNet: ligand-binding site classification with off-the-shelf deep neural network.

Bioinformatics (Oxford, England) May 1, 2020
MOTIVATION: Fast and accurate classification of ligand-binding sites in proteins with respect to the class of binding molecules is invaluable not only to the automatic functional annotation of large datasets of protein structures but also to projects...
Proteins Molecular Structure Ligands Binding Sites Neural Networks, Computer
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Uncovering tissue-specific binding features from differential deep learning.

Nucleic acids research Mar 18, 2020
Transcription factors (TFs) can bind DNA in a cooperative manner, enabling a mutual increase in occupancy. Through this type of interaction, alternative binding sites can be preferentially bound in different tissues to regulate tissue-specific expres...
Binding Sites Homeodomain Proteins Gene Expression Regulation, Developmental Chromatin Immunoprecipitation Embryo, Mammalian Organ Specificity Protein Isoforms Animals Deep Learning Models, Genetic Branchial Region Poisson Distribution Protein Binding Myeloid Ecotropic Viral Integration Site 1 Protein RNA Mice High-Throughput Nucleotide Sequencing Computational Biology
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A computational method for design of connected catalytic networks in proteins.

Protein science : a publication of the Protein Society Dec 1, 2019
Computational design of new active sites has generally proceeded by geometrically defining interactions between the reaction transition state(s) and surrounding side-chain functional groups which maximize transition-state stabilization, and then sear...
Neural Networks, Computer Proteins Databases, Protein Binding Sites Models, Molecular Biocatalysis Hydrogen Bonding
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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...
Neural Networks, Computer Algorithms Peptides Attention Binding Sites Protein Binding Computational Biology Histocompatibility Antigens Class I
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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...
Binding Sites Protein Binding Proteins DNA 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...
MicroRNAs RNA, Messenger Models, Genetic Support Vector Machine Humans HeLa Cells Databases, Genetic Gene Knockdown Techniques Software Binding Sites Computational Biology Gene Knockout Techniques 3' Untranslated Regions
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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 Humans Gene Expression Regulation Transcription Factors Deep Learning DNA 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...
Protein Conformation, beta-Strand Molecular Sequence Annotation Models, Molecular Software Sequence Alignment Protein Binding Internet Gene Ontology Sequence Homology, Amino Acid Proteins Amino Acid Sequence Binding Sites Protein Interaction Domains and Motifs History, 21st Century 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 Software Protein Conformation, alpha-Helical Protein Binding Protein Conformation, beta-Strand Binding Sites Proteins Benchmarking Thermodynamics Internet Humans Datasets as Topic Mutation, Missense Machine Learning Crystallography, X-Ray Protein Interaction Mapping
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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...
Proteins Internet Benchmarking Amino Acid Sequence Ligands Datasets as Topic Binding Sites Humans Machine Learning Software Protein Binding Protein Conformation, beta-Strand Thermodynamics Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical
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