Gene selection from microarray data for cancer classification--a machine learning approach.
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A Review of Feature Selection and Feature Extraction Methods Applied on Microarray DataBioinformatic screening of autoimmune disease genes and protein structure prediction with FAMS for drug discoveryHigh-dimensional pharmacogenetic prediction of a continuous trait using machine learning techniques with application to warfarin dose prediction in African AmericansIdentification and optimization of classifier genes from multi-class earthworm microarray datasetThe LIM and SH3 domain protein family: structural proteins or signal transducers or both?Using simple artificial intelligence methods for predicting amyloidogenesis in antibodiesRecursive cluster elimination (RCE) for classification and feature selection from gene expression data.Classification and biomarker identification using gene network modules and support vector machinesApplication of LogitBoost Classifier for Traceability Using SNP Chip DataRNA-Seq Count Data Modelling by Grey Relational Analysis and Nonparametric Gaussian ProcessA comparative study of different machine learning methods on microarray gene expression dataIdentifying genes that contribute most to good classification in microarrays.Very Important Pool (VIP) genes--an application for microarray-based molecular signatures.Gene expression profiling in limb-girdle muscular dystrophy 2AAn integrated method for cancer classification and rule extraction from microarray data.Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins.Accurate molecular classification of cancer using simple rulesOptimization based tumor classification from microarray gene expression data.Informative gene selection and direct classification of tumor based on Chi-square test of pairwise gene interactions.Microarray-based cancer prediction using single genesNetwork-based Prediction of Cancer under Genetic StormImproving accuracy for cancer classification with a new algorithm for genes selection.CorSig: a general framework for estimating statistical significance of correlation and its application to gene co-expression analysis.Analyzing kernel matrices for the identification of differentially expressed genes.Binary matrix shuffling filter for feature selection in neuronal morphology classificationiRDA: a new filter towards predictive, stable, and enriched candidate genes.SCoRS--A Method Based on Stability for Feature Selection and Mapping inNeuroimaging [corrected].Gene selection for cancer classification with the help of beesNeuropsychological test selection for cognitive impairment classification: A machine learning approachUncovering metabolic pathways relevant to phenotypic traits of microbial genomes.Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector MachineIdentification of protein functions using a machine-learning approach based on sequence-derived properties.Applications of Bayesian gene selection and classification with mixtures of generalized singular g-priors.Prediction of candidate primary immunodeficiency disease genes using a support vector machine learning approach.Identifying high-dimensional biomarkers for personalized medicine via variable importance ranking.Biomarker discovery using statistically significant gene setsPredicting future biomass yield in Miscanthus using the carbohydrate metabolic profile as a biomarker.RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers.Homeobox protein HB9 binds to the prostaglandin E receptor 2 promoter and inhibits intracellular cAMP mobilization in leukemic cells.Penalized model-based clustering with unconstrained covariance matrices.
P2860
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P2860
Gene selection from microarray data for cancer classification--a machine learning approach.
description
2005 nî lūn-bûn
@nan
2005 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2005 թվականի փետրվարին 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
Gene selection from microarray ...... --a machine learning approach.
@ast
Gene selection from microarray ...... --a machine learning approach.
@en
type
label
Gene selection from microarray ...... --a machine learning approach.
@ast
Gene selection from microarray ...... --a machine learning approach.
@en
prefLabel
Gene selection from microarray ...... --a machine learning approach.
@ast
Gene selection from microarray ...... --a machine learning approach.
@en
P2093
P50
P1476
Gene selection from microarray ...... n--a machine learning approach
@en
P2093
P356
10.1016/J.COMPBIOLCHEM.2004.11.001
P577
2005-02-01T00:00:00Z