tailieunhanh - Báo cáo y học: "Consensus clustering and functional interpretation of gene-expression data"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: Consensus clustering and functional interpretation of gene-expression data. | Method Open Access Consensus clustering and functional interpretation of gene-expression data Stephen Swift Allan Tucker Veronica Vinciotti Nigel Martin Christine Orengo Xiaohui Liu and Paul Kellam Addresses Department of Information Systems and Computing Brunel University Uxbridge UB8 3PH UK. School of Computer Science and Information Systems Birkbeck College London WC1E 7HX UK. Department of Biochemistry and Molecular Biology University College London London WC1E 6BT UK. Virus Genomics and Bioinformatics Group Department of Infection Windeyer Institute 46 Cleveland Street University College London London W1T 4JF UK. Correspondence Paul Kellam. E-mail Published I November 2004 Genome Biology 2004 5 R94 The electronic version of this article is the complete one and can be found online at http 2004 5 11 R94 Received 4 December 2003 Revised 15 March 2004 Accepted I3 September 2004 2004 Swift et al. licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 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 NFkB and the unfolded protein response in certain B-cell lymphomas. Background There are many practical applications that involve the grouping of a set of objects into a number of mutually exclusive subsets. Methods to achieve the partitioning of objects .

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