Evaluating Between-Pathway Models with Expression Data

Authors:
Benjamin J. Hescott;Mark D. Leiserson;Lenore J. Cowen;Donna K. Slonim
Affiliations:
Department of Computer Science, Tufts University,;Department of Computer Science, Tufts University,;Department of Computer Science, Tufts University,;Department of Computer Science, Tufts University,
Venue:
RECOMB 2'09 Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology
Year:
2009

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Abstract

Between-Pathway Models (BPMs) are network motifs consisting of pairs of putative redundant pathways. In this paper, we show how adding another source of high-throughput data, microarray gene expression data from knockout experiments, allows us to identify a compensatory functional relationship between genes from the two BPM pathways. We evaluate the quality of the BPMs from four different studies, and we describe how our methods might be extended to refine pathways.