Physical Module Networks: an integrative approach for reconstructing transcription regulation
Name
Novershtern-2011-Physical Module Networks.pdf
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836.63 KB
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Author(s)
Regev, Aviv
Novershtern, Noa
Friedman, Nir
Date Issued
July 2011
Journal
Bioinformatics
Publisher
Oxford University Press (OUP)
Citation
Novershtern, N., A. Regev, and N. Friedman. “Physical Module Networks: An Integrative Approach for Reconstructing Transcription Regulation.” Bioinformatics 27.13 (2011): i177–i185.
Version
Final published version
Abstract
Motivation: Deciphering the complex mechanisms by which regulatory networks control gene expression remains a major challenge. While some studies infer regulation from dependencies between the expression levels of putative regulators and their targets, others focus on measured physical interactions.
Results: Here, we present Physical Module Networks, a unified framework that combines a Bayesian model describing modules of co-expressed genes and their shared regulation programs, and a physical interaction graph, describing the protein–protein interactions and protein-DNA binding events that coherently underlie this regulation. Using synthetic data, we demonstrate that a Physical Module Network model has similar recall and improved precision compared to a simple Module Network, as it omits many false positive regulators. Finally, we show the power of Physical Module Networks to reconstruct meaningful regulatory pathways in the genetically perturbed yeast and during the yeast cell cycle, as well as during the response of primary epithelial human cells to infection with H1N1 influenza.
Availability: The PMN software is available, free for academic use at http://www.compbio.cs.huji.ac.il/PMN/.
Contact: aregev@broad.mit.edu; nirf@cs.huji.ac.il
MIT Department
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution Non-Commercial
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DOI of Published Version
https://doi.org/10.1093/bioinformatics/btr222
