RLSynC: Offline–Online Reinforcement Learning for Synthon Completion-Reference-Cited by-同舟云学术

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RLSynC: Offline–Online Reinforcement Learning for Synthon Completion

Published:2024-08-18 Issue:17 Volume:64 Page:6723-6735
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Baker Frazier N.¹,Chen Ziqi¹,Adu-Ampratwum Daniel²^ORCID,Ning Xia¹²³⁴^ORCID

Affiliation:

1. Department of Computer Science and Engineering, College of Engineering, The Ohio State University, Columbus, Ohio 43210, United States

2. Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, United States

3. Translational Data Analytics Institute, The Ohio State University, Columbus, Ohio 43210, United States

4. Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio 43210, United States

Funder

U.S. National Library of Medicine

Division of Information and Intelligent Systems

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00554

Reference44 articles.

1. AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning

2. Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks

3. Permutation Invariant Graph-to-Sequence Model for Template-Free Retrosynthesis and Reaction Prediction

4. Root-aligned SMILES: a tight representation for chemical reaction prediction

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