about
Computational enzyme design approaches with significant biological outcomes: progress and challengesThree-dimensional structures of membrane proteins from genomic sequencingPredicting helix-helix interactions from residue contacts in membrane proteinsIntegrated analysis of residue coevolution and protein structure in ABC transportersMechanical network in titin immunoglobulin from force distribution analysisProbabilistic grammatical model for helix‐helix contact site classificationDeciphering membrane protein structures from protein sequencesIdentification of specificity determining residues in peptide recognition domains using an information theoretic approach applied to large-scale binding mapsPrediction of membrane protein structures with complex topologies using limited constraintsIntegration of evolutionary features for the identification of functionally important residues in major facilitator superfamily transportersCOMSAT: Residue contact prediction of transmembrane proteins based on support vector machines and mixed integer linear programming.Detecting coevolution without phylogenetic trees? Tree-ignorant metrics of coevolution perform as well as tree-aware metrics.Analysis of the impact of solvent on contacts prediction in proteins.Correlated mutations: a hallmark of phenotypic amino acid substitutions.Conserved and variable correlated mutations in the plant MADS protein network.Lipid exposure prediction enhances the inference of rotational angles of transmembrane helices.Development of scoring functions for antibody sequence assessment and optimization.Dissecting domain-specific evolutionary pressure profiles of transient receptor potential vanilloid subfamily members 1 to 4Protein sector analysis for the clustering of disease-associated mutationsReassessing a sparse energetic network within a single protein domain.Intramolecular allosteric communication in dopamine D2 receptor revealed by evolutionary amino acid covariation.High-accuracy prediction of transmembrane inter-helix contacts and application to GPCR 3D structure modeling.Single-spanning transmembrane domains in cell growth and cell-cell interactions: More than meets the eye?Computational studies of membrane proteins: models and predictions for biological understanding.Robust enzyme design: bioinformatic tools for improved protein stability.CorMut: an R/Bioconductor package for computing correlated mutations based on selection pressure.Predicting structurally conserved contacts for homologous proteins using sequence conservation filtersRHYTHM--a server to predict the orientation of transmembrane helices in channels and membrane-coils.MemBrain-contact 2.0: A new two-stage machine learning model for the prediction enhancement of transmembrane protein residue contacts in the full chain.Pivotal Advance: Avian colony-stimulating factor 1 (CSF-1), interleukin-34 (IL-34), and CSF-1 receptor genes and gene products.TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers.Comparative analysis of sequence covariation methods to mine evolutionary hubs: examples from selected GPCR families.Learning generative models for protein fold families.Modeling and Validation of Transmembrane Protein Structures
P2860
Q24273262-E53564E1-C90E-4DAD-8A21-FD4F77CC2DAFQ24630589-4461E9E1-F3AB-4FE7-AB35-C5E624E4D416Q24645534-663D06C7-3C32-475C-9FEA-BD8AFE446E55Q27303593-FC0AB3A7-852C-4C9D-85EC-6D1F5A37A876Q27335952-70F7F9D6-7FD6-4E78-B27B-EB44E2DA0DC0Q27498962-6FA84A3C-1975-410F-8CE6-8A2AC9FAFA0CQ27499691-B02F651A-F39A-4932-A9B1-A2C8BEC673A1Q30010258-F1F40CE9-3E8A-4A29-9C8D-08D47214B271Q30374712-D466750D-6704-43F3-96EC-AC6A1FF29CDCQ30381269-5CD70BDC-4973-4DB1-9079-4555E9C0F1E2Q30383444-CBFC0604-A9CE-493F-8B9A-9746F3D5E54FQ33389536-323F5F75-3E11-4C3E-BF45-C2D6BFDF73D1Q33430498-38590550-5D85-413F-9B3B-A245F1A7E5E9Q33700653-944E58AC-33BE-4C33-A23D-7AFB8DC52BD5Q33729839-20253321-FCF0-4133-A49E-7DDDDD47128EQ35013462-2020982C-EF58-4B09-8192-5D67F1A42FFEQ35034881-EB04085B-4353-40C7-BA9A-38E9C463BE3FQ35354373-CE11CDA1-3821-4D9A-81E6-263D2D7B95B6Q35537938-0E73AFCF-8192-464F-98A1-A883BCB1C77EQ36534506-D788F0CB-6BB3-408D-8E61-B14AF36845F4Q36770547-5B46227A-C11A-4E73-8D9F-DCA529CD362AQ37212925-DB3E38A8-4CEA-4CB2-BFCC-AE77B4287F02Q37764644-DF4DBC7B-E4C8-4782-BF42-D303D6DAFF56Q37952425-1AFC644B-6AF6-45C4-AE98-14B81C937393Q38294224-68CBCCE8-1517-4EE7-81D1-ACAC51AD61C7Q42221440-5D7AD633-B854-495A-860A-C8B04D769CF5Q42550838-C583EEB8-8913-49D0-9F77-DE0B2FF9FD69Q43103617-7FC99AA8-2C35-42EB-9337-C63AFFA203A6Q45945296-EEE227A1-A98B-42F4-B02B-CE57ABC53B91Q46668932-860D0553-0563-40AD-9B4C-343D8D99BE5DQ47703604-5C2A1F1D-2A04-499B-96CA-E2343C2FF002Q51099046-95A5168F-E7BA-42C9-B97B-020A8E6BD5ABQ51609601-AC6FB033-F9BA-4C29-A91D-A644136FC793Q57207084-19554C1A-C986-4908-81D1-20E25E38CB19
P2860
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年学术文章
@wuu
2007年学术文章
@zh
2007年学术文章
@zh-cn
2007年学术文章
@zh-hans
2007年学术文章
@zh-my
2007年学术文章
@zh-sg
2007年學術文章
@yue
2007年學術文章
@zh-hant
name
Co-evolving residues in membrane proteins.
@en
Co-evolving residues in membrane proteins.
@nl
type
label
Co-evolving residues in membrane proteins.
@en
Co-evolving residues in membrane proteins.
@nl
prefLabel
Co-evolving residues in membrane proteins.
@en
Co-evolving residues in membrane proteins.
@nl
P2093
P2860
P50
P356
P1433
P1476
Co-evolving residues in membrane proteins.
@en
P2093
Angelika Fuchs
Dmitrij Frishman
Matan Kalman
P2860
P304
P356
10.1093/BIOINFORMATICS/BTM515
P407
P577
2007-12-01T00:00:00Z