Assessment of network module identification across complex diseases

<p dir="ltr">Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different type...

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Bibliographic Details
Main Author:	Sarvenaz Choobdar (18602821) (author)
Other Authors:	The DREAM Module Identification Challenge Consortium (18602824) (author), Mehmet E. Ahsen (18602827) (author), Jake Crawford (14846212) (author), Mattia Tomasoni (4227274) (author), Tao Fang (434629) (author), David Lamparter (606695) (author), Junyuan Lin (13017369) (author), Benjamin Hescott (475948) (author), Xiaozhe Hu (18602830) (author), Johnathan Mercer (18602833) (author), Ted Natoli (1339764) (author), Rajiv Narayan (4635193) (author), Aravind Subramanian (712720) (author), Jitao D. Zhang (14913645) (author), Gustavo Stolovitzky (239041) (author), Zoltán Kutalik (174641) (author), Kasper Lage (42180) (author), Donna K. Slonim (14636480) (author), Julio Saez-Rodriguez (25229) (author), Lenore J. Cowen (18602836) (author), Sven Bergmann (20384) (author), Daniel Marbach (366952) (author)
Published:	2019
Subjects:	Biological sciences Bioinformatics and computational biology Bioinformatics gene networks protein networks module identification disease relevance DREAM Challenge
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Assessment of network module identification across complex diseases

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