Reacon: a template- and cluster-based framework for reaction condition prediction

Zihan Wang, Kangjie Lin, Jianfeng Pei and Luhua Lai

Chem. Sci., 2025, 16, 854
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Multistep retrosynthesis combining a disconnection aware triple transformer loop with a route penalty score guided tree search

David Kreutter and Jean-Louis Reymond

Chem. Sci., 2023, 14, 9959
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ORDerly: Data Sets and Benchmarks for Chemical Reaction Data

Daniel S. Wigh, Joe Arrowsmith, Alexander Pomberger, Kobi C. Felton and Alexei A. Lapkin

J. Chem. Inf. Model., 2024, 64, 3790
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Application of Transformers in Cheminformatics

Kha-Dinh Luong and Ambuj Singh

J. Chem. Inf. Model., 2024, 64, 4392
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Performance Analysis of Battery State Prediction Based on Improved Transformer and Time Delay Second Estimation Algorithm

Bo Gao, Xiangjun Li, Fang Guo and Xiping Wang

Batteries, 2025, 11, 262
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Predicting Antioxidant Synergism via Artificial Intelligence and Benchtop Data

Lucas Ayres, Tomás Benavidez, Armelle Varillas, Jeb Linton, Daniel C. Whitehead and Carlos D. Garcia

J. Agric. Food Chem., 2023, 71, 15644
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Enhancing Generic Reaction Yield Prediction through Reaction Condition-Based Contrastive Learning

Xiaodan Yin, Chang-Yu Hsieh, Xiaorui Wang, Zhenxing Wu, Qing Ye, Honglei Bao, Yafeng Deng, Hongming Chen, Pei Luo, Huanxiang Liu, Tingjun Hou and Xiaojun Yao

Research, 2024, 7
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Machine learning-guided strategies for reaction conditions design and optimization

Lung-Yi Chen and Yi-Pei Li

Beilstein J. Org. Chem., 2024, 20, 2476
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Machine Learning Empowering Drug Discovery: Applications, Opportunities and Challenges

Xin Qi, Yuanchun Zhao, Zhuang Qi, Siyu Hou and Jiajia Chen

Molecules, 2024, 29, 903
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Recent Advancements in the Application of Artificial Intelligence in Drug Molecular Generation and Synthesis Planning

Buyong Ma, Yiguo Wang, Xingzi Li, Chang Shen, Hao Lin, Chenxi Du, Shanlin Yang, Ruoqing Zeng, Xuyang Tang, Jinglei Hu, Yukun Yang, Jingwen Wang, Jiawei Zhu, Xingqian Shan, Yu Zhang and Jiaqing Hu

Pharmaceutical Fronts, 2024, 06, e394
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Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditions

Lung-Yi Chen and Yi-Pei Li

J Cheminform, 2024, 16
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Completion of partial chemical equations

Federico Zipoli, Zeineb Ayadi, Philippe Schwaller, Teodoro Laino and Alain C Vaucher

Mach. Learn.: Sci. Technol., 2024, 5, 025071
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Challenging Reaction Prediction Models to Generalize to Novel Chemistry

John Bradshaw, Anji Zhang, Babak Mahjour, David E. Graff, Marwin H. S. Segler and Connor W. Coley

ACS Cent. Sci., 2025, 11, 539
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General Chemically Intuitive Atom- and Bond-Level DFT Descriptors for Machine Learning Approaches to Reaction Condition Prediction

Miguel Nouman, Richard B. Canty, Brent A. Koscher, Matthew A. McDonald and Klavs F. Jensen

J. Chem. Inf. Model., 2025, 65, 6499
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Do Chemformers Dream of Organic Matter? Evaluating a Transformer Model for Multistep Retrosynthesis

Annie M. Westerlund, Siva Manohar Koki, Supriya Kancharla, Alessandro Tibo, Lakshidaa Saigiridharan, Mikhail Kabeshov, Rocío Mercado and Samuel Genheden

J. Chem. Inf. Model., 2024, 64, 3021
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Developing BioNavi for Hybrid Retrosynthesis Planning

Tao Zeng, Zhehao Jin, Shuangjia Zheng, Tao Yu and Ruibo Wu

JACS Au, 2024, 4, 2492
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Computer‐Aided Synthesis Planning (CASP) and Machine Learning: Optimizing Chemical Reaction Conditions

Yu Han, Mingjing Deng, Ke Liu, Jia Chen, Yuting Wang, Yu‐Ning Xu and Longyang Dian

Chemistry A European J, 2024
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