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Organic synthesis is one of the key stumbling blocks in medicinal chemistry.
Corey, E. J.; Long, A. K.; Rubenstein, S. D. Computer-assisted analysis in organic synthesis. Science 1985
1985
Earlier work this paper cites.
Weininger, D. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. Journal of chemical information and computer sciences 1988
1988
Earlier work this paper cites.
Weininger, D.; Weininger, A.; Weininger, J. L. SMILES. 2. Algorithm for generation of unique SMILES notation. Journal of chemical information and computer sciences 1989
1989
Earlier work this paper cites.
Satoh, H.; Funatsu, K. SOPHIA, a knowledge base-guided reaction prediction system-utilization of a knowledge base derived from a reaction database. Journal of chemical information and computer sciences 1995
1995
Earlier work this paper cites.
Bohacek, R. S.; McMartin, C.; Guida, W. C. The art and practice of structure-based drug design: a molecular modeling perspective. Medicinal research reviews 1996
1996
Earlier work this paper cites.
Papineni, K.; Roukos, S.; Ward, T.; Zhu, W.-J. BLEU: a method for automatic evaluation of machine translation. Proceedings of the 40th annual meeting on association for computational linguistics. 2002; pp 311–318
2002
Earlier work this paper cites.
Charest, M. G.; Lerner, C. D.; Brubaker, J. D.; Siegel, D. R.; Myers, A. G. A convergent enantioselective route to structurally diverse 6-deoxytetracycline antibiotics. Science 2005
2005
Earlier work this paper cites.
Lowe, D. M. Extraction of chemical structures and reactions from the literature. Ph.D. thesis, University of Cambridge, 2012
2012
Earlier work this paper cites.
Chen, W. L.; Chen, D. Z.; Taylor, K. T. Automatic reaction mapping and reaction center detection. Wiley Interdisciplinary Reviews: Computational Molecular Science 2013
2013
Earlier work this paper cites.
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
Schneider, N.; Lowe, D. M.; Sayle, R. A.; Landrum, G. A. Development of a novel fingerprint for chemical reactions and its application to large-scale reaction classification and similarity. Journal of chemical information and modeling 2015
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
Wei, J. N.; Duvenaud, D.; Aspuru-Guzik, A. Neural networks for the prediction of organic chemistry reactions. ACS central science 2016
2016
Earlier work this paper cites.
Szymkuć, S.; Gajewska, E. P.; Klucznik, T.; Molga, K.; Dittwald, P.; Startek, M.; Bajczyk, M.; Grzybowski, B. A. Computer-Assisted Synthetic Planning: The End of the Beginning. Angewandte Chemie International Edition 2016
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
Schneider, N.; Lowe, D. M.; Sayle, R. A.; Tarselli, M. A.; Landrum, G. A. Big data from pharmaceutical patents: a computational analysis of medicinal chemists’ bread and butter. J. Med. Chem. 2016
2016
Cited alongside, same era.
Schneider, N.; Stiefl, N.; Landrum, G. A. What’s what: The (nearly) definitive guide to reaction role assignment. Journal of chemical information and modeling 2016
2016
Cited alongside, same era.
Szegedy, C.; Vanhoucke, V.; Ioffe, S.; Shlens, J.; Wojna, Z. Rethinking the inception architecture for computer vision. Proceedings of the IEEE conference on computer vision and pattern recognition. 2016; pp 2818–2826
2016
Cited alongside, same era.
2017
Cited alongside, same era.
Gómez-Bombarelli, R.; Wei, J. N.; Duvenaud, D.; Hernández-Lobato, J. M.; Sánchez-Lengeling, B.; Sheberla, D.; Aguilera-Iparraguirre, J.; Hirzel, T. D.; Adams, R. P.; Aspuru-Guzik, A. Automatic chemical design using a data-driven continuous representation of molecules. ACS central science 2018
2018
Closest in time.
Popova, M.; Isayev, O.; Tropsha, A. Deep reinforcement learning for de novo drug design. Science advances 2018
2018
Closest in time.
Blaschke, T.; Olivecrona, M.; Engkvist, O.; Bajorath, J.; Chen, H. Application of generative autoencoder in de novo molecular design. Molecular informatics 2018
2018
Closest in time.
2018
Closest in time.
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2017
Cited alongside, same era.
Coley, C. W.; Barzilay, R.; Jaakkola, T. S.; Green, W. H.; Jensen, K. F. Prediction of organic reaction outcomes using machine learning. ACS central science 2017
2017
Cited alongside, same era.
Segler, M. H.; Waller, M. P. Neural-Symbolic Machine Learning for Retrosynthesis and Reaction Prediction. Chemistry–A European Journal 2017
2017
Cited alongside, same era.
Jin, W.; Coley, C.; Barzilay, R.; Jaakkola, T. Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network. Advances in Neural Information Processing Systems. 2017; pp 2604–2613
2017
Cited alongside, same era.
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; Polosukhin, I. Attention is all you need. Advances in Neural Information Processing Systems. 2017; pp 6000–6010
2017
Cited alongside, same era.
Landrum, G. et al. Rdkit/Rdkit: 2017_09_1 (Q3 2017) Release. 2017; https://zenodo.org/record/1004356#.Wd3LDY6l2EI
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Klein, G.; Kim, Y.; Deng, Y.; Senellart, J.; Rush, A. M. OpenNMT: Open-Source Toolkit for Neural Machine Translation. Proc. ACL. 2017
2017
Cited alongside, same era.
2018
Closest in time.
Engkvist, O.; Norrby, P.-O.; Selmi, N.; Lam, Y.-h.; Peng, Z.; Sherer, E. C.; Amberg, W.; Erhard, T.; Smyth, L. A. Computational prediction of chemical reactions: current status and outlook. Drug discovery today 2018
2018
Closest in time.
Coley, C. W.; Green, W. H.; Jensen, K. F. Machine Learning in Computer-Aided Synthesis Planning. Accounts of chemical research 2018
2018
Closest in time.
Grzybowski, B. A.; Szymkuć, S.; Gajewska, E. P.; Molga, K.; Dittwald, P.; Wołos, A.; Klucznik, T. Chematica: A Story of Computer Code That Started to Think like a Chemist. Chem 2018
2018
Closest in time.
2018
Closest in time.
2018
Closest in time.
Schwaller, P.; Gaudin, T.; Lanyi, D.; Bekas, C.; Laino, T. “Found in Translation”: Predicting Outcomes of Complex Organic Chemistry Reactions using Neural Sequence-to-Sequence Models. Chemical Science 2018
2018
Closest in time.
Annotated Transformer. http://nlp.seas.harvard.edu/2018/04/03/attention.html
2018
Closest in time.
Liu, Y.; Zhou, L.; Wang, Y.; Zhao, Y.; Zhang, J.; Zong, C. A Comparable Study on Model Averaging, Ensembling and Reranking in NMT. CCF International Conference on Natural Language Processing and Chinese Computing. 2018; pp 299–308
2018
Closest in time.
Segler, M. H.; Preuss, M.; Waller, M. P. Planning chemical syntheses with deep neural networks and symbolic AI. Nature 2018
2018
Closest in time.
Coley, C. W.; Jin, W.; Rogers, L.; Jamison, T. F.; Jaakkola, T. S.; Green, W. H.; Barzilay, R.; Jensen, K. F. A graph-convolutional neural network model for the prediction of chemical reactivity. Chemical science 2019
2019
Closest in time.