APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility.
about
Prediction of protein-protein interaction sites by random forest algorithm with mRMR and IFSPrediction of S-glutathionylation sites based on protein sequencesCharacterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organizationInterolog interfaces in protein-protein dockingA sequence-based computational model for the prediction of the solvent accessible surface area for α-helix and β-barrel transmembrane residues.ECMIS: computational approach for the identification of hotspots at protein-protein interfaces.Exploiting a reduced set of weighted average features to improve prediction of DNA-binding residues from 3D structures.Relationship between amino acid properties and functional parameters in olfactory receptors and discrimination of mutants with enhanced specificity.ProDis-ContSHC: learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval.Predictions of hot spot residues at protein-protein interfaces using support vector machines.PredHS: a web server for predicting protein-protein interaction hot spots by using structural neighborhood properties.DBAC: a simple prediction method for protein binding hot spots based on burial levels and deeply buried atomic contacts.Protein painting reveals solvent-excluded drug targets hidden within native protein-protein interfaces.A semi-supervised boosting SVM for predicting hot spots at protein-protein interfacesProtein localization prediction using random walks on graphs.Locating tandem repeats in weighted sequences in proteinsHot spots in a network of functional sites.Mining the bladder cancer-associated genes by an integrated strategy for the construction and analysis of differential co-expression networks.Integrating water exclusion theory into β contacts to predict binding free energy changes and binding hot spotsCRF-based models of protein surfaces improve protein-protein interaction site predictionsCo-Occurring Atomic Contacts for the Characterization of Protein Binding Hot SpotsPrediction of heme binding residues from protein sequences with integrative sequence profilesRelationship between hot spot residues and ligand binding hot spots in protein-protein interfaces.PredPhos: an ensemble framework for structure-based prediction of phosphorylation sitesPredicting hot spots in protein interfaces based on protrusion index, pseudo hydrophobicity and electron-ion interaction pseudopotential features.Boosting prediction performance of protein-protein interaction hot spots by using structural neighborhood propertiesA simple recipe for the non-expert bioinformaticist for building experimentally-testable hypotheses for proteins with no known homologs.SKEMPI: a Structural Kinetic and Energetic database of Mutant Protein Interactions and its use in empirical models.A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces.A new scoring function for protein-protein docking that identifies native structures with unprecedented accuracy.Predictions of Protein-Protein Interfaces within Membrane Protein Complexes.BeAtMuSiC: Prediction of changes in protein-protein binding affinity on mutations.Comprehensive experimental and computational analysis of binding energy hot spots at the NF-κB essential modulator/IKKβ protein-protein interface.Identification of bacteriophage virion proteins by the ANOVA feature selection and analysis.A computational tool to predict the evolutionarily conserved protein-protein interaction hot-spot residues from the structure of the unbound protein.A hadoop-based method to predict potential effective drug combination.Solvent-accessible surface area: How well can be applied to hot-spot detection?Are hot-spots occluded from water?Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences.Prediction of hot spots in protein interfaces using a random forest model with hybrid features.
P2860
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P2860
APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility.
description
2010 nî lūn-bûn
@nan
2010 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
APIS: accurate prediction of h ...... ex with solvent accessibility.
@ast
APIS: accurate prediction of h ...... ex with solvent accessibility.
@en
APIS: accurate prediction of h ...... ex with solvent accessibility.
@nl
type
label
APIS: accurate prediction of h ...... ex with solvent accessibility.
@ast
APIS: accurate prediction of h ...... ex with solvent accessibility.
@en
APIS: accurate prediction of h ...... ex with solvent accessibility.
@nl
prefLabel
APIS: accurate prediction of h ...... ex with solvent accessibility.
@ast
APIS: accurate prediction of h ...... ex with solvent accessibility.
@en
APIS: accurate prediction of h ...... ex with solvent accessibility.
@nl
P2860
P356
P1433
P1476
APIS: accurate prediction of h ...... dex with solvent accessibility
@en
P2093
De-Shuang Huang
Xing-Ming Zhao
P2860
P2888
P356
10.1186/1471-2105-11-174
P577
2010-04-08T00:00:00Z
P5875
P6179
1035410163