Inferring causal molecular networks: empirical assessment through a community-based effort.
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Authors
Heiser, Laura M
Cokelaer, Thomas
Unger, Michael
Nesser, Nicole K
Carlin, Daniel E
Zhang, Yang
Sokolov, Artem
Paull, Evan O
Wong, Chris K
Bivol, Adrian
Wang, Haizhou
Zhu, Fan
Afsari, Bahman
Favorov, Alexander V
Lee, Wai Shing
Hu, Chenyue W
Long, Byron L
Noren, David P
Bisberg, Alexander J
HPN-DREAM Consortium,
Mills, Gordon B
Gray, Joe W
Norman, Thea
Qutub, Amina A
Fertig, Elana J
Guan, Yuanfang
Stuart, Joshua M
Spellman, Paul T
Koeppl, Heinz
Stolovitzky, Gustavo
Mukherjee, Sach
Publication Date
2016-04Journal Title
Nature methods
ISSN
1548-7091
Volume
13
Issue
4
Pages
310-318
Language
eng
Type
Article
This Version
VoR
Physical Medium
Print-Electronic
Metadata
Show full item recordCitation
Hill, S., Heiser, L. M., Cokelaer, T., Unger, M., Nesser, N. K., Carlin, D. E., Zhang, Y., et al. (2016). Inferring causal molecular networks: empirical assessment through a community-based effort.. Nature methods, 13 (4), 310-318. https://doi.org/10.1038/nmeth.3773
Keywords
HPN-DREAM Consortium, Tumor Cells, Cultured, Humans, Neoplasms, Gene Expression Profiling, Protein Interaction Mapping, Computational Biology, Systems Biology, Causality, Signal Transduction, Algorithms, Models, Biological, Computer Simulation, Software, Gene Regulatory Networks
Sponsorship
MRC (unknown)
Identifiers
External DOI: https://doi.org/10.1038/nmeth.3773
This record's URL: https://www.repository.cam.ac.uk/handle/1810/278785
Rights
Attribution-NonCommercial-ShareAlike 4.0 International
Licence URL: http://creativecommons.org/licenses/by-nc-sa/4.0/
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