J. Born, M. Manica, A. Oskooei—Equal Contributions.
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References
Manica, M., et al.: Toward explainable anticancer compound sensitivity prediction via multimodal attention-based convolutional encoders. Molecular Pharmaceutics (2019). ACS Publications
Scannell, J.W., Blanckley, A., Boldon, H., Warrington, B.: Diagnosing the decline in pharmaceutical R&D efficiency. Nat. Rev. Drug Discovery 11(3), 191 (2012)
Schneider, G.: Mind and machine in drug design. Nat. Mach. Intell. 1, 128–130 (2019)
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Born, J., Manica, M., Oskooei, A., Cadow, J., Rodríguez Martínez, M. (2020). PaccMannRL: Designing Anticancer Drugs From Transcriptomic Data via Reinforcement Learning. In: Schwartz, R. (eds) Research in Computational Molecular Biology. RECOMB 2020. Lecture Notes in Computer Science(), vol 12074. Springer, Cham. https://doi.org/10.1007/978-3-030-45257-5_18
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