  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.
