A novel approach to predicting protein structural classes in a (20-1)-D amino acid composition space.
about
Improved Chou-Fasman method for protein secondary structure predictionSemi-supervised protein subcellular localizationCharacterization of protein secondary structure from NMR chemical shiftsSupport vector machines for predicting protein structural classEsub8: a novel tool to predict protein subcellular localizations in eukaryotic organismspSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties.Prediction of protein structural class with Rough Sets.APSLAP: an adaptive boosting technique for predicting subcellular localization of apoptosis proteinSupport vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity searchPredicting drug-target interaction networks based on functional groups and biological featuresAnalysis and prediction of the metabolic stability of proteins based on their sequential features, subcellular locations and interaction networksNR-2L: a two-level predictor for identifying nuclear receptor subfamilies based on sequence-derived featuresPredicting functions of proteins in mouse based on weighted protein-protein interaction network and protein hybrid propertiesClassification and analysis of regulatory pathways using graph property, biochemical and physicochemical property, and functional propertyPrediction of antimicrobial peptides based on sequence alignment and feature selection methodsA multi-label classifier for predicting the subcellular localization of gram-negative bacterial proteins with both single and multiple sitesiNuc-PhysChem: a sequence-based predictor for identifying nucleosomes via physicochemical propertiesiGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networkingiEzy-drug: a web server for identifying the interaction between enzymes and drugs in cellular networkingSCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.Customised fragments libraries for protein structure prediction based on structural class annotations.Structural alphabets for protein structure classification: a comparison studyAn optimal structure-discriminative amino acid index for protein fold recognitionCombining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations.Classification of protein quaternary structure by functional domain composition.Protein structural class prediction based on an improved statistical strategy.Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences.Prediction of protein structural classes for low-homology sequences based on predicted secondary structure.Analysis and prediction of translation rate based on sequence and functional features of the mRNA.Some insights into protein structural class prediction.Immunization of mice with a TolA-like surface protein of Trypanosoma cruzi generates CD4(+) T-cell-dependent parasiticidal activity.iDNA-Prot: identification of DNA binding proteins using random forest with grey model.iDNA-Prot|dis: identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid compositionHepatitis C virus network based classification of hepatocellular cirrhosis and carcinomaAccurate prediction of protein structural class.An ensemble method for predicting subnuclear localizations from primary protein structures.PLPD: reliable protein localization prediction from imbalanced and overlapped datasets.Studies of protein-protein interfaces: a statistical analysis of the hydrophobic effectString kernels for protein sequence comparisons: improved fold recognition.Prediction of complex super-secondary structure βαβ motifs based on combined features.
P2860
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P2860
A novel approach to predicting protein structural classes in a (20-1)-D amino acid composition space.
description
1995 nî lūn-bûn
@nan
1995 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
1995 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
1995年の論文
@ja
1995年論文
@yue
1995年論文
@zh-hant
1995年論文
@zh-hk
1995年論文
@zh-mo
1995年論文
@zh-tw
1995年论文
@wuu
name
A novel approach to predicting ...... amino acid composition space.
@ast
A novel approach to predicting ...... amino acid composition space.
@en
A novel approach to predicting protein structural classes in a
@nl
type
label
A novel approach to predicting ...... amino acid composition space.
@ast
A novel approach to predicting ...... amino acid composition space.
@en
A novel approach to predicting protein structural classes in a
@nl
prefLabel
A novel approach to predicting ...... amino acid composition space.
@ast
A novel approach to predicting ...... amino acid composition space.
@en
A novel approach to predicting protein structural classes in a
@nl
P356
P1433
P1476
A novel approach to predicting ...... amino acid composition space.
@en
P2093
P304
P356
10.1002/PROT.340210406
P407
P577
1995-04-01T00:00:00Z