Armadillo: domain boundary prediction by amino acid composition.
about
FIEFDom: a transparent domain boundary recognition system using a fuzzy mean operatorPrediction of antimicrobial peptides based on sequence alignment and feature selection methodsImproving the performance of DomainDiscovery of protein domain boundary assignment using inter-domain linker indexIdentifying foldable regions in protein sequence from the hydrophobic signal.Improved general regression network for protein domain boundary prediction.PDP-CON: prediction of domain/linker residues in protein sequences using a consensus approach.DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.Identification of putative domain linkers by a neural network - application to a large sequence database.Hinge Atlas: relating protein sequence to sites of structural flexibility.Ab initio and homology based prediction of protein domains by recursive neural networksMathematical model for empirically optimizing large scale production of soluble protein domainsDomSVR: domain boundary prediction with support vector regression from sequence information aloneDIRProt: a computational approach for discriminating insecticide resistant proteins from non-resistant proteins.ThreaDom: extracting protein domain boundary information from multiple threading alignments.OPUS-Dom: applying the folding-based method VECFOLD to determine protein domain boundaries.ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly.Domain structure of Lassa virus L protein.Prediction of aptamer-target interacting pairs with pseudo-amino acid composition.IS-Dom: a dataset of independent structural domains automatically delineated from protein structures.Understanding the role of domain-domain linkers in the spatial orientation of domains in multi-domain proteins.Fast H-DROP: A thirty times accelerated version of H-DROP for interactive SVM-based prediction of helical domain linkers.H-DROP: an SVM based helical domain linker predictor trained with features optimized by combining random forest and stepwise selection.Using directed evolution to improve the solubility of the C-terminal domain of Escherichia coli aminopeptidase P. Implications for metal binding and protein stability.
P2860
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P2860
Armadillo: domain boundary prediction by amino acid composition.
description
2005 nî lūn-bûn
@nan
2005 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2005 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2005年の論文
@ja
2005年論文
@yue
2005年論文
@zh-hant
2005年論文
@zh-hk
2005年論文
@zh-mo
2005年論文
@zh-tw
2005年论文
@wuu
name
Armadillo: domain boundary prediction by amino acid composition.
@ast
Armadillo: domain boundary prediction by amino acid composition.
@en
type
label
Armadillo: domain boundary prediction by amino acid composition.
@ast
Armadillo: domain boundary prediction by amino acid composition.
@en
prefLabel
Armadillo: domain boundary prediction by amino acid composition.
@ast
Armadillo: domain boundary prediction by amino acid composition.
@en
P2093
P1476
Armadillo: domain boundary prediction by amino acid composition.
@en
P2093
Christopher W V Hogue
Howard J Feldman
P304
P356
10.1016/J.JMB.2005.05.037
P407
P577
2005-07-01T00:00:00Z