Knowledge-based analysis of microarray gene expression data by using support vector machines
about
Distinguishing protein-coding from non-coding RNAs through support vector machines.Improving the Caenorhabditis elegans genome annotation using machine learningA parallel genetic algorithm for single class pattern classification and its application for gene expression profiling in Streptomyces coelicolorGene function classification using Bayesian models with hierarchy-based priorsTumour class prediction and discovery by microarray-based DNA methylation analysisSpectral biclustering of microarray data: coclustering genes and conditionsGeneMANIA: a real-time multiple association network integration algorithm for predicting gene functionMicroarrays and molecular markers for tumor classificationMulti-class cancer classification by total principal component regression (TPCR) using microarray gene expression dataApplication of independent component analysis to microarraysAFM 4.0: a toolbox for DNA microarray analysisMulticlass classification of microarray data with repeated measurements: application to cancerPermutation-validated principal components analysis of microarray dataThe functional landscape of mouse gene expressionCo-regulation of mouse genes predicts functionMany accurate small-discriminatory feature subsets exist in microarray transcript data: biomarker discovery.Postgenomics: Proteomics and Bioinformatics in Cancer ResearchVisANT: an online visualization and analysis tool for biological interaction dataSupport vector machines for predicting protein structural classQuantifying the relationship between co-expression, co-regulation and gene functionPredicting binding sites of hydrolase-inhibitor complexes by combining several methodsQuadratic regression analysis for gene discovery and pattern recognition for non-cyclic short time-course microarray experimentsCancer characterization and feature set extraction by discriminative margin clusteringCorrelation and prediction of gene expression level from amino acid and dipeptide composition of its proteinQuantitative inference of dynamic regulatory pathways via microarray dataPrediction of MHC class I binding peptides, using SVMHCTowards precise classification of cancers based on robust gene functional expression profilesEvaluation of gene importance in microarray data based upon probability of selectionPathwayExplorer: web service for visualizing high-throughput expression data on biological pathways.Application of genomics to toxicology researchDiscriminating different classes of toxicants by transcript profilingOptimized between-group classification: a new jackknife-based gene selection procedure for genome-wide expression data.Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm.Protein subcellular localization prediction for Gram-negative bacteria using amino acid subalphabets and a combination of multiple support vector machines.Identifying cooperative transcriptional regulations using protein-protein interactionsUsing decision forest to classify prostate cancer samples on the basis of SELDI-TOF MS data: assessing chance correlation and prediction confidence.Kernel-based machine learning protocol for predicting DNA-binding proteinsMissing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding schemeMicroarray missing data imputation based on a set theoretic framework and biological knowledgeAn approach for clustering gene expression data with error information.
P2860
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P2860
Knowledge-based analysis of microarray gene expression data by using support vector machines
description
2000 nî lūn-bûn
@nan
2000 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2000 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2000年の論文
@ja
2000年論文
@yue
2000年論文
@zh-hant
2000年論文
@zh-hk
2000年論文
@zh-mo
2000年論文
@zh-tw
2000年论文
@wuu
name
Knowledge-based analysis of mi ...... using support vector machines
@ast
Knowledge-based analysis of mi ...... using support vector machines
@en
Knowledge-based analysis of mi ...... using support vector machines.
@nl
type
label
Knowledge-based analysis of mi ...... using support vector machines
@ast
Knowledge-based analysis of mi ...... using support vector machines
@en
Knowledge-based analysis of mi ...... using support vector machines.
@nl
prefLabel
Knowledge-based analysis of mi ...... using support vector machines
@ast
Knowledge-based analysis of mi ...... using support vector machines
@en
Knowledge-based analysis of mi ...... using support vector machines.
@nl
P2093
P2860
P3181
P356
P1476
Knowledge-based analysis of mi ...... using support vector machines
@en
P2093
P2860
P304
P3181
P356
10.1073/PNAS.97.1.262
P407
P577
2000-01-01T00:00:00Z