title: Evaluating between-pathway models with expression data.
abstract: Between-pathway models (BPMs) are network motifs consisting of pairs of putative redundant pathways. In this article, 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.
authors.affiliation: Department of Computer Science, Tufts University, Medford, Massachusetts 02155, USA. hescott@cs.tufts.edu
authors.forename: B J
authors.initials: BJ
authors.lastname: Hescott
authors.forename: M D M
authors.initials: MD
authors.lastname: Leiserson
authors.forename: L J
authors.initials: LJ
authors.lastname: Cowen
authors.forename: D K
authors.initials: DK
authors.lastname: Slonim
mesh_terms: D016000:Cluster Analysis; D017353:Gene Deletion; D020869:Gene Expression Profiling; D015966:Gene Expression Regulation, Fungal; D055786:Gene Knockout Techniques; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008957:Models, Genetic; D015203:Reproducibility of Results; D012441:Saccharomyces cerevisiae / Q000235:genetics*