TY - JOUR T1 - Estimating cellular pathways from an ensemble of heterogeneous data sources JF - bioRxiv DO - 10.1101/006478 SP - 006478 AU - Alexander M. Franks AU - Florian Markowetz AU - Edoardo Airoldi Y1 - 2014/01/01 UR - http://biorxiv.org/content/early/2014/06/23/006478.abstract N2 - Building better models of cellular pathways is one of the major challenges of systems biology and functional genomics. There is a need for methods to build on established expert knowledge and reconcile it with results of high-throughput studies. Moreover, the available data sources are heterogeneous and need to be combined in a way specific for the part of the pathway in which they are most informative. Here, we present a compartment specific strategy to integrate edge, node and path data for the refinement of a network hypothesis. Specifically, we use a local-move Gibbs sampler for refining pathway hypotheses from a compendium of heterogeneous data sources, including novel methodology for integrating protein attributes. We demonstrate the utility of this approach in a case study of the pheromone response MAPK pathway in the yeast S. cerevisiae. ER -