Nonparametric methods for identifying differentially expressed genes in microarray data.
about
SED, a normalization free method for DNA microarray data analysisMulticlass discovery in array dataLeveraging two-way probe-level block design for identifying differential gene expression with high-density oligonucleotide arraysTests for finding complex patterns of differential expression in cancers: towards individualized medicineImproving identification of differentially expressed genes in microarray studies using information from public databasesNonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experimentsMining gene expression data by interpreting principal components.Alterations in gene expression in T1 alpha null lung: a model of deficient alveolar sac developmentEvaluating microarray-based classifiers: an overviewRank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experimentsA graph-theoretic approach for identifying non-redundant and relevant gene markers from microarray data using multiobjective binary PSOGenome-scale identification of Caenorhabditis elegans regulatory elements by tiling-array mapping of DNase I hypersensitive sites.Variation in fiberoptic bead-based oligonucleotide microarrays: dispersion characteristics among hybridization and biological replicate samples.Biological assessment of robust noise models in microarray data analysis.Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray dataSemi-supervised discovery of differential genes.GRACOMICS: software for graphical comparison of multiple results with omics data.Computational strategies for analyzing data in gene expression microarray experiments.Differential and trajectory methods for time course gene expression data.Use of extreme patient samples for outcome prediction from gene expression data.Comparison of various statistical methods for identifying differential gene expression in replicated microarray data.Determination of strongly overlapping signaling activity from microarray data.A stable gene selection in microarray data analysis.Tilescope: online analysis pipeline for high-density tiling microarray data.Identification of phenotype-relevant differentially expressed genes in breast cancer demonstrates enhanced quantile discretization protocol's utility in multi-platform microarray data integration.Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes.The L1-version of the Cramér-von Mises test for two-sample comparisons in microarray data analysisPrincipal components analysis based methodology to identify differentially expressed genes in time-course microarray data.ArraySolver: an algorithm for colour-coded graphical display and Wilcoxon signed-rank statistics for comparing microarray gene expression dataPredicting survival within the lung cancer histopathological hierarchy using a multi-scale genomic model of developmentA biological question and a balanced (orthogonal) design: the ingredients to efficiently analyze two-color microarrays with Confirmatory Factor Analysis.The impact of sample imbalance on identifying differentially expressed genes.Deciphering protein-protein interactions. Part I. Experimental techniques and databases.Integrated analysis of independent gene expression microarray datasets improves the predictability of breast cancer outcomeA Population Proportion approach for ranking differentially expressed genes.A novel method incorporating gene ontology information for unsupervised clustering and feature selection.A factor graph nested effects model to identify networks from genetic perturbations.Statistical methods for detecting differentially abundant features in clinical metagenomic samples.A new class of mixture models for differential gene expression in DNA microarray data.Integrating multiple microarray data for cancer pathway analysis using bootstrapping K-S test.
P2860
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P2860
Nonparametric methods for identifying differentially expressed genes in microarray data.
description
2002 nî lūn-bûn
@nan
2002 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2002 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
2002年の論文
@ja
2002年論文
@yue
2002年論文
@zh-hant
2002年論文
@zh-hk
2002年論文
@zh-mo
2002年論文
@zh-tw
2002年论文
@wuu
name
Nonparametric methods for identifying differentially expressed genes in microarray data.
@ast
Nonparametric methods for identifying differentially expressed genes in microarray data.
@en
type
label
Nonparametric methods for identifying differentially expressed genes in microarray data.
@ast
Nonparametric methods for identifying differentially expressed genes in microarray data.
@en
prefLabel
Nonparametric methods for identifying differentially expressed genes in microarray data.
@ast
Nonparametric methods for identifying differentially expressed genes in microarray data.
@en
P50
P356
P1433
P1476
Nonparametric methods for identifying differentially expressed genes in microarray data.
@en
P2093
Mitchell E Garber
P304
P356
10.1093/BIOINFORMATICS/18.11.1454
P407
P577
2002-11-01T00:00:00Z