Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprote...

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Detalles Bibliográficos
Autores principales: Hill, Steven M, Heiser, Laura M, Cokelaer, Thomas, Unger, Michael, Nesser, Nicole K, Carlin, Daniel E, Zhang, Yang, Sokolov, Artem, Paull, Evan O, Wong, Chris K, Graim, Kiley, Bivol, Adrian, Wang, Haizhou, Zhu, Fan, Afsari, Bahman, Danilova, Ludmila V, Favorov, Alexander V, Lee, Wai Shing, Taylor, Dane, Hu, Chenyue W, Long, Byron L, Noren, David P, Bisberg, Alexander J, Mills, Gordon B, Gray, Joe W, Kellen, Michael, Norman, Thea, Friend, Stephen, Qutub, Amina A, Fertig, Elana J, Guan, Yuanfang, Song, Mingzhou, Stuart, Joshua M, Spellman, Paul T, Koeppl, Heinz, Stolovitzky, Gustavo, Saez-Rodriguez, Julio, Mukherjee, Sach
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4854847/
https://www.ncbi.nlm.nih.gov/pubmed/26901648
http://dx.doi.org/10.1038/nmeth.3773

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4854847/
https://www.ncbi.nlm.nih.gov/pubmed/26901648
http://dx.doi.org/10.1038/nmeth.3773

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