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September 2018 Refining cellular pathway models using an ensemble of heterogeneous data sources
Alexander M. Franks, Florian Markowetz, Edoardo M. Airoldi
Ann. Appl. Stat. 12(3): 1361-1384 (September 2018). DOI: 10.1214/16-AOAS915


Improving current models and hypotheses 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 new high-throughput studies. Moreover, the available sources of data are heterogeneous, and the data need to be integrated in different ways depending on which part of the pathway they are most informative for. In this paper, we introduce a compartment specific strategy to integrate edge, node and path data for refining a given network hypothesis. To carry out inference, we use a local-move Gibbs sampler for updating the pathway hypothesis from a compendium of heterogeneous data sources, and a new network regression idea 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 M. Franks. Florian Markowetz. Edoardo M. Airoldi. "Refining cellular pathway models using an ensemble of heterogeneous data sources." Ann. Appl. Stat. 12 (3) 1361 - 1384, September 2018.


Received: 1 March 2014; Revised: 1 January 2016; Published: September 2018
First available in Project Euclid: 11 September 2018

zbMATH: 06979635
MathSciNet: MR3852681
Digital Object Identifier: 10.1214/16-AOAS915

Rights: Copyright © 2018 Institute of Mathematical Statistics


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Vol.12 • No. 3 • September 2018
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