Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties.
about
Computational prediction of type III and IV secreted effectors in gram-negative bacteriaA survey of computational intelligence techniques in protein function predictionPredicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structureL1pred: a sequence-based prediction tool for catalytic residues in enzymes with the L1-logreg classifierEXIA2: web server of accurate and rapid protein catalytic residue prediction.Novel feature for catalytic protein residues reflecting interactions with other residuesFunctional region prediction with a set of appropriate homologous sequences--an index for sequence selection by integrating structure and sequence information with spatial statistics.Identification of catalytic residues using a novel feature that integrates the microenvironment and geometrical location properties of residues.Accurate prediction of protein catalytic residues by side chain orientation and residue contact density.Protein structure based prediction of catalytic residuesAutomatic prediction of catalytic residues by modeling residue structural neighborhood.Using shifts in amino acid frequency and substitution rate to identify latent structural characters in base-excision repair enzymesSelective prediction of interaction sites in protein structures with THEMATICS.Predicting active site residue annotations in the Pfam database.Fast dynamics perturbation analysis for prediction of protein functional sites.Protein meta-functional signatures from combining sequence, structure, evolution, and amino acid property informationDetection of protein catalytic residues at high precision using local network properties.Partial order optimum likelihood (POOL): maximum likelihood prediction of protein active site residues using 3D Structure and sequence propertiesAccurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systemsResBoost: characterizing and predicting catalytic residues in enzymesRegression applied to protein binding site prediction and comparison with classificationPredictive models of autism spectrum disorder based on brain regional cortical thickness.Active site prediction using evolutionary and structural information.Networks of high mutual information define the structural proximity of catalytic sites: implications for catalytic residue identification.New methods to measure residues coevolution 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.Sequence polymorphism, segmental recombination and toggling amino acid residues within the DBL3X domain of the VAR2CSA placental malaria antigen.Evolutionary approach to predicting the binding site residues of a protein from its primary sequenceStructure-based identification of catalytic residues.LIBRUS: combined machine learning and homology information for sequence-based ligand-binding residue prediction.Biochemical functional predictions for protein structures of unknown or uncertain functionAn overview of the prediction of protein DNA-binding sitesCPC: assess the protein-coding potential of transcripts using sequence features and support vector machine.Normal Modes Expose Active Sites in Enzymes.Machine learning classifier for identification of damaging missense mutations exclusive to human mitochondrial DNA-encoded polypeptides.Enhanced performance in prediction of protein active sites with THEMATICS and support vector machinesOn the structural context and identification of enzyme catalytic residues.E1DS: catalytic site prediction based on 1D signatures of concurrent conservation.Cell cycle kinases predicted from conserved biophysical properties
P2860
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P2860
Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties.
description
2006 nî lūn-bûn
@nan
2006 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2006 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2006年の論文
@ja
2006年論文
@yue
2006年論文
@zh-hant
2006年論文
@zh-hk
2006年論文
@zh-mo
2006年論文
@zh-tw
2006年论文
@wuu
name
Prediction of catalytic residu ...... nce and structural properties.
@ast
Prediction of catalytic residu ...... nce and structural properties.
@en
type
label
Prediction of catalytic residu ...... nce and structural properties.
@ast
Prediction of catalytic residu ...... nce and structural properties.
@en
prefLabel
Prediction of catalytic residu ...... nce and structural properties.
@ast
Prediction of catalytic residu ...... nce and structural properties.
@en
P2860
P356
P1433
P1476
Prediction of catalytic residu ...... nce and structural properties.
@en
P2093
Cathy H Wu
Natalia V Petrova
P2860
P2888
P356
10.1186/1471-2105-7-312
P577
2006-06-21T00:00:00Z
P5875
P6179
1053004630