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GraphGR: A graph neural network to predict the effect of pharmacotherapy on the cancer cell growth
Manali Singha, Limeng Pu, Abd-El-Monsif Shawky, Konstantin Busch, Hsiao-Chun Wu, J. Ramanujam, View ORCID ProfileMichal Brylinski
doi: https://doi.org/10.1101/2020.05.20.107458
Manali Singha
1Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
Limeng Pu
2Center for Computation and Technology, Louisiana State University, Baton Rouge, LA 70803, USA
Abd-El-Monsif Shawky
1Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
3Department of Cell Biology, National Research Centre, 12622 Giza, Egypt
Konstantin Busch
4Division of Computer Science and Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
Hsiao-Chun Wu
5Division of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
J. Ramanujam
2Center for Computation and Technology, Louisiana State University, Baton Rouge, LA 70803, USA
5Division of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
Michal Brylinski
1Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
2Center for Computation and Technology, Louisiana State University, Baton Rouge, LA 70803, USA
Posted May 23, 2020.
GraphGR: A graph neural network to predict the effect of pharmacotherapy on the cancer cell growth
Manali Singha, Limeng Pu, Abd-El-Monsif Shawky, Konstantin Busch, Hsiao-Chun Wu, J. Ramanujam, Michal Brylinski
bioRxiv 2020.05.20.107458; doi: https://doi.org/10.1101/2020.05.20.107458
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