RT Journal Article
SR Electronic
T1 Estimating cellular pathways from an ensemble of heterogeneous data sources
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 006478
DO 10.1101/006478
A1 Alexander M. Franks
A1 Florian Markowetz
A1 Edoardo Airoldi
YR 2014
UL http://biorxiv.org/content/early/2014/06/23/006478.abstract
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.