svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identifica

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. Results: Using the singular value decomposition (SVD) technique, we developed a new computational tool, named svdPPCS (SVD-based Pattern Pairing and Chart Splitting), to identify conserved and divergent co-expression modules of two sets of microarray experiments. In the proposed m...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Wensheng Zhang, Andrea Edwards, Wei Fan, Dongxiao Zhu, Kun Zhang
• Keywords: Biological Categories, BMCBI 2010, Gene Expression, Gene Modules