Prophetic Granger Causality to infer gene regulatory networks.

We introduce a novel method called Prophetic Granger Causality (PGC) for inferring gene regulatory networks (GRNs) from protein-level time series data. The method uses an L1-penalized regression adaptation of Granger Causality to model protein levels as a function of time, stimuli, and other perturb...

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Bibliographic Details
Main Authors: Daniel E Carlin, Evan O Paull, Kiley Graim, Christopher K Wong, Adrian Bivol, Peter Ryabinin, Kyle Ellrott, Artem Sokolov, Joshua M Stuart
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0170340
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