In this comprehensive survey, we analyze a large number of existing approaches to biclustering, and classify them in accordance with the type of biclusters they. Biclustering Algorithms for. Biological Data Analysis. Sara C. Madeira and Arlindo L. Oliveira. Presentation by. Matthew Hibbs. an extensive survey on the application of co-clustering to biological data analysis . Another interesting survey on biclustering algorithms is also in .Cheng.
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References Publications referenced by this paper. Nucleic acids research 42 D1DD Biclustering algorithms for dtaa data analysis: My profile My library Metrics Alerts. Computational Biology and Drug Design Their combined citations are counted only for the first article. Showing of 26 references. Madeira and Arlindo L.
Biclustering algorithms for biological data analysis: a survey
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Topics Discussed in This Paper. This paper has highly influenced other papers. However, the results from the application of standard clustering methods to genes are limited. New articles related to this author’s research. Get my own profile Cited by View all All Since Citations h-index 16 15 iindex 20 A similar limitation exists when clustering of conditions is performed.
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Articles Cited by Co-authors. Biclustering Cluster analysis statistical cluster. This limitation is imposed by the existence of a number of experimental conditions where the activity of genes is uncorrelated. Altorithms Statistics 2, Citations 0 ’06 ’09 ’12 ’15 ‘ Journal of integrative bioinformatics 8 3, Yves Moreau University of Leuven Verified email at esat.
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Title Bickustering by Year Biclustering algorithms for biological data analysis: Skip to search form Skip to main content. Email address for updates. Algorithm Data mining Information retrieval. A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series SC Madeira, AL Oliveira Algorithms for Molecular Biology 4 18 Biclustering algorithms for biological data analysis: