An empirical Bayesian approach for identifying differential coexpression in high-throughput experiments
type: Item
instance of: scholarly article
zbMATH Open document ID: 1251.62042
author: John A. Dawson
author: Christina Kendziorski
published in: Biometrics
publication date: 2012-09-14T00:00:00Z
full work available at URL: pmc3482945
Mathematics Subject Classification ID: 62P10
Mathematics Subject Classification ID: 62C12
Mathematics Subject Classification ID: 92D10
Mathematics Subject Classification ID: 92C40
Mathematics Subject Classification ID: 92C50
zbMATH DE Number: 6082618
zbMATH Keywords: coexpression
zbMATH Keywords: empirical Bayes
zbMATH Keywords: gene expressions
zbMATH Keywords: meta-analysis
zbMATH Keywords: microarrays
zbMATH Keywords: prostate cancer
describes a project that uses: R
describes a project that uses: Bioconductor
describes a project that uses: EBarrays
describes a project that uses: mclust
describes a project that uses: gcrma
describes a project that uses: BOBYQA
describes a project that uses: CoXpress
MaRDI profile type: Publication
OpenAlex ID: W2047820517
Wikidata QID: Q36352750
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DOI: 10.1111/J.1541-0420.2011.01688.X
title: An empirical Bayesian approach for identifying differential coexpression in high-throughput experiments
description: scientific article; zbMATH DE number 6082618