PT  - JOURNAL ARTICLE
AU  - Alexander M. Franks
AU  - Florian Markowetz
AU  - Edoardo Airoldi
TI  - Estimating cellular pathways from an ensemble of heterogeneous data sources
AID  - 10.1101/006478
DP  - 2014 Jan 01
TA  - bioRxiv
PG  - 006478
4099  - http://biorxiv.org/content/early/2014/06/23/006478.short
4100  - http://biorxiv.org/content/early/2014/06/23/006478.full
AB  - 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.