Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino acid pairs.
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Semi-supervised protein subcellular localizationLocTree2 predicts localization for all domains of lifeProtein subcellular localization prediction of eukaryotes using a knowledge-based approachEsub8: a novel tool to predict protein subcellular localizations in eukaryotic organismsTMB-Hunt: an amino acid composition based method to screen proteomes for beta-barrel transmembrane proteinsRefining protein subcellular localizationLOCSVMPSI: a web server for subcellular localization of eukaryotic proteins using SVM and profile of PSI-BLASTProtein subcellular localization prediction for Gram-negative bacteria using amino acid subalphabets and a combination of multiple support vector machines.pSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties.iLoc-Euk: a multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteinsMultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid compositionSherLoc: high-accuracy prediction of protein subcellular localization by integrating text and protein sequence dataPrediction of membrane transport proteins and their substrate specificities using primary sequence informationPlus ça change - evolutionary sequence divergence predicts protein subcellular localization signalsA multi-label predictor for identifying the subcellular locations of singleplex and multiplex eukaryotic proteinsMachine learning for in silico virtual screening and chemical genomics: new strategiesSemi-supervised prediction of protein subcellular localization using abstraction augmented Markov modelsRanking the quality of protein structure models using sidechain based network propertiesngLOC: an n-gram-based Bayesian method for estimating the subcellular proteomes of eukaryotes.mGOASVM: Multi-label protein subcellular localization based on gene ontology and support vector machinesA graphical model approach to automated classification of protein subcellular location patterns in multi-cell images.Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence.Evaluation and comparison of mammalian subcellular localization prediction methods.Protein subcellular localization prediction based on compartment-specific features and structure conservation.'Unite and conquer': enhanced prediction of protein subcellular localization by integrating multiple specialized toolsSubcellular location prediction of proteins using support vector machines with alignment of block sequences utilizing amino acid composition.ProLoc-GO: utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localizationSupervised learning method for the prediction of subcellular localization of proteins using amino acid and amino acid pair composition.Identification of proteins secreted by malaria parasite into erythrocyte using SVM and PSSM profiles.HECTAR: a method to predict subcellular targeting in heterokonts.ESLpred2: improved method for predicting subcellular localization of eukaryotic proteins.MiRTif: a support vector machine-based microRNA target interaction filter.A method to improve protein subcellular localization prediction by integrating various biological data sources.MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction.Identification of type 2 diabetes-associated combination of SNPs using support vector machineFGsub: Fusarium graminearum protein subcellular localizations predicted from primary structuresTESTLoc: protein subcellular localization prediction from EST data.Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae.Going from where to why--interpretable prediction of protein subcellular localization.An ensemble classifier for eukaryotic protein subcellular location prediction using gene ontology categories and amino acid hydrophobicity
P2860
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P2860
Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino acid pairs.
description
2003 nî lūn-bûn
@nan
2003年の論文
@ja
2003年学术文章
@wuu
2003年学术文章
@zh-cn
2003年学术文章
@zh-hans
2003年学术文章
@zh-my
2003年学术文章
@zh-sg
2003年學術文章
@yue
2003年學術文章
@zh
2003年學術文章
@zh-hant
name
Prediction of protein subcellu ...... no acids and amino acid pairs.
@en
Prediction of protein subcellu ...... no acids and amino acid pairs.
@nl
type
label
Prediction of protein subcellu ...... no acids and amino acid pairs.
@en
Prediction of protein subcellu ...... no acids and amino acid pairs.
@nl
prefLabel
Prediction of protein subcellu ...... no acids and amino acid pairs.
@en
Prediction of protein subcellu ...... no acids and amino acid pairs.
@nl
P356
P1433
P1476
Prediction of protein subcellu ...... no acids and amino acid pairs.
@en
P2093
Keun-Joon Park
Minoru Kanehisa
P304
P356
10.1093/BIOINFORMATICS/BTG222
P407
P577
2003-09-01T00:00:00Z