Issue 46, 2021

Data undersampling models for the efficient rule-based retrosynthetic planning

Abstract

Computer-aided retrosynthetic planning for organic molecules, which is based on a large synthetic database, is a significant part of the recent development of autonomous robotic chemists. As in other AI fields, however, the class imbalance problem in the dataset affects the prediction performance of retrosynthetic paths. Here, we demonstrate that applying undersampling models to the imbalanced reaction dataset can improve the prediction of retrosynthetic templates for target molecules. We report improvements in the top-1 and top-10 prediction accuracies by 13.8% (13.1, 5.4%) and 8.8% (6.9, 2.4%) for undersampling based on the similarity (random, dissimilarity) clustering of molecular structures of products, respectively. These results demonstrate the importance of deep understanding of the statistical distribution, internal structure, and sampling for the training dataset. For practical applications, the target-oriented undersampling model is proposed and confirmed by the improved prediction performance of 9.3 and 4.2% for the top-1 and top-10 accuracies, respectively.

Graphical abstract: Data undersampling models for the efficient rule-based retrosynthetic planning

Supplementary files

Article information

Article type
Paper
Submitted
07 Aug 2021
Accepted
08 Nov 2021
First published
08 Nov 2021

Phys. Chem. Chem. Phys., 2021,23, 26510-26518

Data undersampling models for the efficient rule-based retrosynthetic planning

M. S. Park, D. Lee, Y. Kwon, E. Kim and Y. Choi, Phys. Chem. Chem. Phys., 2021, 23, 26510 DOI: 10.1039/D1CP03630K

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements