Journal
NPJ Systems Biology and Applications
Publication Date
2019
Volume
5
Inclusive Pages
6
Document Type
Open Access Publication
DOI
10.1038/s41540-019-0085-4
Rights and Permissions
egan-Fendt, K. E., Xu, J. L., DiVincenzo, M., Duggan, M. C., Shakya, R., Na, R., . . . Li, F. H. (2019). Synergy from gene expression and network mining (SynGeNet) method predicts synergistic drug combinations for diverse melanoma genomic subtypes. Npj Systems Biology and Applications, 5, 15. doi:10.1038/s41540-019-0085-4 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Recommended Citation
Regan-Fendt, Kelly E.; Xu, Jielin; DiVincenzo, Mallory; Duggan, Megan C.; Shakya, Reena; Na, Ryejung; Carson, William E. III; Payne, Philip R. O.; and Li, Fuhai, "Synergy from gene expression and network mining (SynGeNet) method predicts synergistic drug combinations for diverse melanoma genomic subtypes." NPJ Systems Biology and Applications. 5, 6. (2019).
https://digitalcommons.wustl.edu/open_access_pubs/7647
braflogcpm.txt (113 kB)
nf1logcpm.txt (66 kB)
nraslogcpm.txt (63 kB)
twtlogcpm.txt (67 kB)
.DS_Store (6 kB)
BRAF_rootgenes.txt (1 kB)
NF1_rootgenes.txt (1 kB)
NRAS_rootgenes.txt (1 kB)
TWT_rootgenes.txt (1 kB)
.DS_Store (14 kB)
.Rhistory (1 kB)
License (11 kB)
melanoma_fdadrugs_n633.txt (101763 kB)
README (3 kB)
subUserFunctionsVa2.R (8 kB)
SynGeNet.R (13 kB)
