Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners
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Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability ModelsImproving accuracy of protein contact prediction using balanced network deconvolution.Simultaneous identification of specifically interacting paralogs and interprotein contacts by direct coupling analysis.Membrane protein contact and structure prediction using co-evolution in conjunction with machine learning.Resummed mean-field inference for strongly coupled data.Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1.Inter-Protein Sequence Co-Evolution Predicts Known Physical Interactions in Bacterial Ribosomes and the Trp OperonMaximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity.Predicting protein-protein interactions via multivariate mutual information of protein sequences.Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis.EPSILON-CP: using deep learning to combine information from multiple sources for protein contact prediction.Intramolecular allosteric communication in dopamine D2 receptor revealed by evolutionary amino acid covariation.Identification of Protein-Protein Interactions via a Novel Matrix-Based Sequence Representation Model with Amino Acid Contact Information.Inferring interaction partners from protein sequences.HCV E2 core structures and mAbs: something is still missing.Revealing protein networks and gene-drug connectivity in cancer from direct information.Predicting accurate contacts in thousands of Pfam domain families using PconsC3.Structural propensities of kinase family proteins from a Potts model of residue co-variation.Identifying relevant positions in proteins by Critical Variable Selection.The unexpected structures of hepatitis C virus envelope proteinsBiomolecular coevolution and its applications: Going from structure prediction toward signaling, epistasis, and function.Three-body interactions improve contact prediction within direct-coupling analysis.A generative model for protein contact networks.MISTIC2: comprehensive server to study coevolution in protein families.Humanization of Antibodies using a Statistical Inference Approach
P2860
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P2860
Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners
description
2014 nî lūn-bûn
@nan
2014 թուականի Մարտին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի մարտին հրատարակված գիտական հոդված
@hy
2014年の論文
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2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Fast and accurate multivariate ...... d protein-interaction partners
@ast
Fast and accurate multivariate ...... d protein-interaction partners
@en
type
label
Fast and accurate multivariate ...... d protein-interaction partners
@ast
Fast and accurate multivariate ...... d protein-interaction partners
@en
prefLabel
Fast and accurate multivariate ...... d protein-interaction partners
@ast
Fast and accurate multivariate ...... d protein-interaction partners
@en
P2093
P2860
P50
P1433
P1476
Fast and accurate multivariate ...... d protein-interaction partners
@en
P2093
Andrea Procaccini
Christoph Feinauer
Marco Zamparo
P2860
P304
P356
10.1371/JOURNAL.PONE.0092721
P407
P577
2014-03-24T00:00:00Z