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Correlated Discretized Expression Score: A Method for Identifying Gene Interaction Networks from Time Course Microarray Expression Data

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4 Author(s)
Larsen, P. ; Core Genomics Lab., Illinois Univ., Chicago, IL ; Almasri, E. ; Chen, G. ; Yang Dai

One of the goals of genomic expression analysis is to construct gene interaction networks from microarray data. Time course microarray data is a common place to seek causal relationships between the expression of a regulator and its effect on the expression of its targets. By proposing gene expression patterns of regulator and target genes based on biological expectation of regulatory interactions, it is possible to propose a system to identify these patterns. This system is based on the correlated discretized expression (CDE) score calculated from microarray time course data. The CDE-score is derived by discretizing microarray data to identify significant gene expression changes. The usefulness of this method is demonstrated using a set of hypothetical gene expression data and the analysis of S. cerevisiae cell cycle microarray data

Published in:

Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE

Date of Conference:

Aug. 30 2006-Sept. 3 2006