Integrating Proteomic, Transcriptional, and Interactome Data Reveals Hidden Components of Signaling and Regulatory Networks

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Science Signaling  28 Jul 2009:
Vol. 2, Issue 81, pp. ra40
DOI: 10.1126/scisignal.2000350

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Finding the Missing Links

Constructing signaling networks that are meaningful and useful from high-throughput data sets is a major challenge in systems biology. Huang and Fraenkel present a computational approach based on the prize-collecting Steiner tree (PCST) problem that integrates diverse data sets, and by allowing indirect connections it yields relatively small, but functionally relevant, networks. For the yeast pheromone response pathway, they relate transcription expression data to data from genetic screens and data from phosphoproteomic analysis through a PCST analysis to reveal previously unidentified connections and components not readily apparent from either data set.