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...

Descripción completa

Detalles Bibliográficos
Autores principales: Carlin, Daniel E., Paull, Evan O., Graim, Kiley, Wong, Christopher K., Bivol, Adrian, Ryabinin, Peter, Ellrott, Kyle, Sokolov, Artem, Stuart, Joshua M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5718405/
https://www.ncbi.nlm.nih.gov/pubmed/29211761
http://dx.doi.org/10.1371/journal.pone.0170340

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5718405/
https://www.ncbi.nlm.nih.gov/pubmed/29211761
http://dx.doi.org/10.1371/journal.pone.0170340

Ejemplares similares