Support vector machine approach for protein subcellular localization prediction.
about
Distinguishing protein-coding from non-coding RNAs through support vector machines.Semi-supervised protein subcellular localizationSubcellular localization of CIAPIN1The Escherichia coli proteome: past, present, and future prospectsPSORTdb: a protein subcellular localization database for bacteriaCoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resourcesPredicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositionsPSORT-B: Improving protein subcellular localization prediction for Gram-negative bacteriaAMPDB: the Arabidopsis Mitochondrial Protein DatabaseOntological visualization of protein-protein interactionsBoosting accuracy of automated classification of fluorescence microscope images for location proteomicsEsub8: a novel tool to predict protein subcellular localizations in eukaryotic organismsRefining protein subcellular localizationGPCRsclass: a web tool for the classification of amine type of G-protein-coupled receptorsLOCSVMPSI: 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.Dynamic covariation between gene expression and proteome characteristicsNon-classical protein secretion in bacteria.PhosphoregDB: the tissue and sub-cellular distribution of mammalian protein kinases and phosphatases.An SVM-based system for predicting protein subnuclear localizations.Explaining Support Vector Machines: A Color Based NomogramHCV genotyping using statistical classification approachRNA sequence and two-dimensional structure features required for efficient substrate modification by the Saccharomyces cerevisiae RNA:{Psi}-synthase Pus7p.A survey of computational intelligence techniques in protein function predictionHSEpred: predict half-sphere exposure from protein sequencesPSORTb v.2.0: expanded prediction of bacterial protein subcellular localization and insights gained from comparative proteome analysisMultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid compositionSupport vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity searchC-PAmP: large scale analysis and database construction containing high scoring computationally predicted antimicrobial peptides for all the available plant speciesLearning from Heterogeneous Data Sources: An Application in Spatial ProteomicsA multi-label predictor for identifying the subcellular locations of singleplex and multiplex eukaryotic proteinsMachine learning for in silico virtual screening and chemical genomics: new strategiesSurface proteome analysis and characterization of surface cell antigen (Sca) or autotransporter family of Rickettsia typhi.Recognition of stable protein mutants with 3D stochastic average electrostatic potentials.Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information.Predicting residue-wise contact orders in proteins by support vector regressionRanking the quality of protein structure models using sidechain based network propertiesBioinformatics and Drug Discovery.Using principal component analysis and support vector machine to predict protein structural class for low-similarity sequences via PSSM.
P2860
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P2860
Support vector machine approach for protein subcellular localization prediction.
description
2001 nî lūn-bûn
@nan
2001年の論文
@ja
2001年学术文章
@wuu
2001年学术文章
@zh
2001年学术文章
@zh-cn
2001年学术文章
@zh-hans
2001年学术文章
@zh-my
2001年学术文章
@zh-sg
2001年學術文章
@yue
2001年學術文章
@zh-hant
name
Support vector machine approach for protein subcellular localization prediction.
@en
Support vector machine approach for protein subcellular localization prediction.
@nl
type
label
Support vector machine approach for protein subcellular localization prediction.
@en
Support vector machine approach for protein subcellular localization prediction.
@nl
prefLabel
Support vector machine approach for protein subcellular localization prediction.
@en
Support vector machine approach for protein subcellular localization prediction.
@nl
P356
P1433
P1476
Support vector machine approach for protein subcellular localization prediction.
@en
P304
P356
10.1093/BIOINFORMATICS/17.8.721
P407
P577
2001-08-01T00:00:00Z