A multi-stream network for retrosynthesis prediction

Graphical abstract

References

[1] Coley C W, Rogers L, Green W H, Jensen K F . Computer-assisted retrosynthesis based on molecular similarity. ACS Central Science, 2017, 3( 12): 1237–1245

[2] Segler M H S, Waller M P . Neural-symbolic machine learning for retrosynthesis and reaction prediction. Chemistry-A European Journal, 2017, 23( 25): 5966–5971

[3] Zheng S, Rao J, Zhang Z, Xu J, Yang Y. Predicting retrosynthetic reactions using self-corrected transformer neural networks. Journal of Chemical Information and Modeling, 2022, 60 (1): 47 − 55

[4] Weininger D . SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. Journal of Chemical Information & Computer Sciences, 1988, 28( 1): 31–36

[5] Ye X B, Guan Q, Luo W, Fang L, Lai Z R, Wang J . Molecular substructure graph attention network for molecular property identification in drug discovery. Pattern Recognition, 2022, 128: 108659

[6] Liu B, Ramsundar B, Kawthekar P, Shi J, Gomes J, Nguyen Q L, Ho S, Sloane J, Wender P, Pande V . Retrosynthetic reaction prediction using neural sequence-to-sequence models. ACS Central Science, 2017, 3( 10): 1103–1113

[7] Shi C, Xu M, Guo H, Zhang M, Tang J. A graph to graphs framework for retrosynthesis prediction. In: Proceedings of the 37th International Conference on Machine Learning. 2020, 818

[8] Chen B, Shen T, Jaakkola T S, Barzilay R. Learning to make generalizable and diverse predictions for retrosynthesis. 2019, arXiv preprint arXiv: 1910.09688

RIGHTS & PERMISSIONS

Higher Education Press