Automated prediction of protein function and detection of functional sites from structure.
about
Analyzing effects of naturally occurring missense mutationsA large-scale evaluation of computational protein function predictionProtein molecular function prediction by Bayesian phylogenomics.Molecular mechanisms of disease-causing missense mutationsInferred Biomolecular Interaction Server--a web server to analyze and predict protein interacting partners and binding sitesAccurate protein structure annotation through competitive diffusion of enzymatic functions over a network of local evolutionary similaritiesGlobal mapping of the protein structure space and application in structure-based inference of protein function.Structure-based function inference using protein family-specific fingerprints.Towards fully automated structure-based function prediction in structural genomics: a case studyDBAli tools: mining the protein structure spaceEfficient identification of critical residues based only on protein structure by network analysis.The AnnoLite and AnnoLyze programs for comparative annotation of protein structures.Genome bioinformatic analysis of nonsynonymous SNPsEXIA2: web server of accurate and rapid protein catalytic residue prediction.Detecting evolutionary relationships across existing fold space, using sequence order-independent profile-profile alignments.Exploring the structure and function paradigm.A comprehensive analysis of the structure-function relationship in proteins based on local structure similarity.A new approach to assess and predict the functional roles of proteins across all known structuresNovel feature for catalytic protein residues reflecting interactions with other residuesProtein co-evolution: how do we combine bioinformatics and experimental approaches?Protein function prediction using text-based features extracted from the biomedical literature: the CAFA challengeProtein interactions and ligand binding: from protein subfamilies to functional specificity.Screening for peptide drugs from the natural repertoire of biodiverse protein folds.Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks.Predicting gene ontology functions from protein's regional surface structuresLocal function conservation in sequence and structure spaceAccurate prediction of peptide binding sites on protein surfaces.Conserved residue clusters at protein-protein interfaces and their use in binding site identification.Analysis of spatial and temporal protein expression in the cerebral cortex after ischemia-reperfusion injuryA novel and efficient tool for locating and characterizing protein cavities and binding sites.Active site prediction using evolutionary and structural information.Structural relationships in the lysozyme superfamily: significant evidence for glycoside hydrolase signature motifs.Structural analysis of heme proteins: implications for design and prediction.Chapter 4. Predicting and characterizing protein functions through matching geometric and evolutionary patterns of binding surfaces.A glimpse at the organization of the protein universe.Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy functionKnowledge-based annotation of small molecule binding sites in proteins.Structure-based kernels for the prediction of catalytic residues and their involvement in human inherited disease.High-performance prediction of functional residues in proteins with machine learning and computed input features.Protein docking by the interface structure similarity: how much structure is needed?
P2860
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P2860
Automated prediction of protein function and detection of functional sites from structure.
description
article científic
@ca
article scientifique
@fr
articolo scientifico
@it
artigo científico
@pt
bilimsel makale
@tr
scientific article published on 29 September 2004
@en
vedecký článok
@sk
vetenskaplig artikel
@sv
videnskabelig artikel
@da
vědecký článek
@cs
name
Automated prediction of protei ...... nctional sites from structure.
@en
Automated prediction of protei ...... nctional sites from structure.
@nl
type
label
Automated prediction of protei ...... nctional sites from structure.
@en
Automated prediction of protei ...... nctional sites from structure.
@nl
prefLabel
Automated prediction of protei ...... nctional sites from structure.
@en
Automated prediction of protei ...... nctional sites from structure.
@nl
P2860
P921
P356
P1476
Automated prediction of protei ...... nctional sites from structure.
@en
P2093
Florencio Pazos
Michael J E Sternberg
P2860
P304
14754-14759
P356
10.1073/PNAS.0404569101
P407
P577
2004-09-29T00:00:00Z