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2018 2
2019 3
2020 1
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Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research.
David L, ArĂºs-Pous J, Karlsson J, Engkvist O, Bjerrum EJ, Kogej T, Kriegl JM, Beck B, Chen H. David L, et al. Among authors: bjerrum ej. Front Pharmacol. 2019 Nov 5;10:1303. doi: 10.3389/fphar.2019.01303. eCollection 2019. Front Pharmacol. 2019. PMID: 31749705 Free PMC article. Review.
Datasets and their influence on the development of computer assisted synthesis planning tools in the pharmaceutical domain.
Thakkar A, Kogej T, Reymond JL, Engkvist O, Bjerrum EJ. Thakkar A, et al. Among authors: bjerrum ej. Chem Sci. 2019 Nov 5;11(1):154-168. doi: 10.1039/c9sc04944d. eCollection 2020 Jan 7. Chem Sci. 2019. PMID: 32110367 Free PMC article.
De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping.
Sattarov B, Baskin II, Horvath D, Marcou G, Bjerrum EJ, Varnek A. Sattarov B, et al. Among authors: bjerrum ej. J Chem Inf Model. 2019 Mar 25;59(3):1182-1196. doi: 10.1021/acs.jcim.8b00751. Epub 2019 Mar 5. J Chem Inf Model. 2019. PMID: 30785751
"Ring Breaker": Neural Network Driven Synthesis Prediction of the Ring System Chemical Space.
Thakkar A, Selmi N, Reymond JL, Engkvist O, Bjerrum EJ. Thakkar A, et al. Among authors: bjerrum ej. J Med Chem. 2020 Aug 27;63(16):8791-8808. doi: 10.1021/acs.jmedchem.9b01919. Epub 2020 May 13. J Med Chem. 2020. PMID: 32352286
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