@article {Franks006478, author = {Alexander M. Franks and Florian Markowetz and Edoardo Airoldi}, title = {Estimating cellular pathways from an ensemble of heterogeneous data sources}, elocation-id = {006478}, year = {2014}, doi = {10.1101/006478}, publisher = {Cold Spring Harbor Laboratory}, abstract = {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.}, URL = {https://www.biorxiv.org/content/early/2014/06/23/006478}, eprint = {https://www.biorxiv.org/content/early/2014/06/23/006478.full.pdf}, journal = {bioRxiv} }