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arXiv · 1406.5799

Estimating cellular pathways from an ensemble of heterogeneous data sources

Alexander Franks·Florian Markowetz·Edoardo Airoldi
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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.

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Alexander Franks, Florian Markowetz, Edoardo Airoldi. 2014-06-23. Estimating cellular pathways from an ensemble of heterogeneous data sources. https://arxiv.org/abs/1406.5799

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