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SynergySeq

Integrate transcriptional Drug and Disease Signatures to predict therapeutic compound combinations http://synergyseq.com/ (https://schurerlab.shinyapps.io/synergyseq/)

Citation:

Stathias, V., Jermakowicz, A.M., Maloof, M.E., Forlin, M., Walters, W., Suter, R.K., Durante, M.A., Williams, S.L., Harbour, J.W., Volmar, C.H., et al. (2018). Drug and disease signature integration identifies synergistic combinations in glioblastoma. Nature Communications 9, 5315

Acknowledgements:

This research was supported by grant U54HL127624 awarded by the National Heart, Lung, and Blood Institute through funds provided by the trans-NIH Library of Integrated Network-based Cellular Signatures (LINCS) Program (http://www.lincsproject.org/) and the trans-NIH Big Data to Knowledge (BD2K) initiative (https://datascience.nih.gov/).