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Consensus clustering and functional interpretation of gene-expression data

Swift, S. and Tucker, A. and Vinciotti, V. and Martin, Nigel and Orengo, C.A. and Liu, X. and Kellam, P. (2004) Consensus clustering and functional interpretation of gene-expression data. Genome Biology 5 (11), ISSN 1465-6906.

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Official URL: http://dx.doi.org/10.1186/gb-2004-5-11-r94

Abstract

Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus set of clusters from a number of clustering methods should improve confidence in gene-expression analysis. Here we introduce consensus clustering, which provides such an advantage. When coupled with a statistically based gene functional analysis, our method allowed the identification of novel genes regulated by NFκB and the unfolded protein response in certain B-cell lymphomas.

Item Type: Article
School or Research Centre: Birkbeck Schools and Research Centres > School of Business, Economics & Informatics > Computer Science and Information Systems
Depositing User: Administrator
Date Deposited: 27 Jan 2011 16:17
Last Modified: 17 Apr 2013 12:33
URI: http://eprints.bbk.ac.uk/id/eprint/2991

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