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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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.
|School:||Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems|
|Research Centre:||Structural Molecular Biology, Institute of (ISMB), Birkbeck Knowledge Lab|
|Date Deposited:||27 Jan 2011 16:17|
|Last Modified:||06 Dec 2016 10:32|
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