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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Detalhes bibliográficos
Publicado no:PLoS One
Main Authors: Carlin, Daniel E., Paull, Evan O., Graim, Kiley, Wong, Christopher K., Bivol, Adrian, Ryabinin, Peter, Ellrott, Kyle, Sokolov, Artem, Stuart, Joshua M.
Formato: Artigo
Idioma:Inglês
Publicado em: Public Library of Science 2017
Assuntos:
Research Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5718405/
https://ncbi.nlm.nih.gov/pubmed/29211761
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0170340
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