svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identification |
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Authors: | Wensheng Zhang Andrea Edwards Wei Fan Dongxiao Zhu Kun Zhang |
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Institution: | (1) Department of Computer Science, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA;(2) IBM T.J.Watson Research, 19 Skyline Drive, Hawthorne, NY 10532, USA;(3) Department of Computer Science, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA 70122, USA |
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Abstract: | Background Comparative analysis of gene expression profiling of multiple biological categories, such as different species of organisms
or different kinds of tissue, promises to enhance the fundamental understanding of the universality as well as the specialization
of mechanisms and related biological themes. Grouping genes with a similar expression pattern or exhibiting co-expression
together is a starting point in understanding and analyzing gene expression data. In recent literature, gene module level
analysis is advocated in order to understand biological network design and system behaviors in disease and life processes;
however, practical difficulties often lie in the implementation of existing methods. |
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Keywords: | |
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