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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine Learning in Computer-Aided Synthesis Planning
Connor W. Coley, William H. Green, Klavs F. Jensen
Accounts of Chemical Research (2018) Vol. 51, Iss. 5, pp. 1281-1289
Closed Access | Times Cited: 635

Showing 26-50 of 635 citing articles:

Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks
Shuangjia Zheng, Jiahua Rao, Zhongyue Zhang, et al.
Journal of Chemical Information and Modeling (2019) Vol. 60, Iss. 1, pp. 47-55
Open Access | Times Cited: 212
BigSMILES: A Structurally-Based Line Notation for Describing Macromolecules
Tzyy-Shyang Lin, Connor W. Coley, Hidenobu Mochigase, et al.
ACS Central Science (2019) Vol. 5, Iss. 9, pp. 1523-1531
Open Access | Times Cited: 206
Virtual Chemical Libraries
W. Patrick Walters
Journal of Medicinal Chemistry (2018) Vol. 62, Iss. 3, pp. 1116-1124
Closed Access | Times Cited: 201
Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis
Xiwen Jia, Allyson Lynch, Yuheng Huang, et al.
Nature (2019) Vol. 573, Iss. 7773, pp. 251-255
Closed Access | Times Cited: 199
A Structure-Based Platform for Predicting Chemical Reactivity
Frederik Sandfort, Felix Strieth‐Kalthoff, Marius Kühnemund, et al.
Chem (2020) Vol. 6, Iss. 6, pp. 1379-1390
Open Access | Times Cited: 195
Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis
Thomas J. Struble, Juan C. Alvarez, Scott P. Brown, et al.
Journal of Medicinal Chemistry (2020) Vol. 63, Iss. 16, pp. 8667-8682
Open Access | Times Cited: 189
Automatic retrosynthetic route planning using template-free models
Kangjie Lin, Youjun Xu, Jianfeng Pei, et al.
Chemical Science (2020) Vol. 11, Iss. 12, pp. 3355-3364
Open Access | Times Cited: 188
RetroBioCat as a computer-aided synthesis planning tool for biocatalytic reactions and cascades
William Finnigan, Lorna J. Hepworth, Sabine L. Flitsch, et al.
Nature Catalysis (2021) Vol. 4, Iss. 2, pp. 98-104
Open Access | Times Cited: 185
A Brief Introduction to Chemical Reaction Optimization
Connor J. Taylor, Alexander Pomberger, Kobi Felton, et al.
Chemical Reviews (2023) Vol. 123, Iss. 6, pp. 3089-3126
Open Access | Times Cited: 183
Machine-Learning-Driven Synthesis of Carbon Dots with Enhanced Quantum Yields
Yu Han, Bijun Tang, Liang Wang, et al.
ACS Nano (2020) Vol. 14, Iss. 11, pp. 14761-14768
Open Access | Times Cited: 181
Process systems engineering – The generation next?
Efstratios N. Pistikopoulos, Ana Paula Barbosa‐Póvoa, Jay H. Lee, et al.
Computers & Chemical Engineering (2021) Vol. 147, pp. 107252-107252
Closed Access | Times Cited: 178
Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
John A. Keith, Valentín Vassilev-Galindo, Bingqing Cheng, et al.
Chemical Reviews (2021) Vol. 121, Iss. 16, pp. 9816-9872
Open Access | Times Cited: 176
Autonomous Discovery in the Chemical Sciences Part I: Progress
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
Angewandte Chemie International Edition (2019) Vol. 59, Iss. 51, pp. 22858-22893
Open Access | Times Cited: 175
A field guide to flow chemistry for synthetic organic chemists
Luca Capaldo, Zhenghui Wen, Timothy Noël
Chemical Science (2023) Vol. 14, Iss. 16, pp. 4230-4247
Open Access | Times Cited: 175
Learning Retrosynthetic Planning through Simulated Experience
John S. Schreck, Connor W. Coley, Kyle J. M. Bishop
ACS Central Science (2019) Vol. 5, Iss. 6, pp. 970-981
Open Access | Times Cited: 171
Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns
Tânia Cova, Alberto A. C. C. Pais
Frontiers in Chemistry (2019) Vol. 7
Open Access | Times Cited: 157
RDChiral: An RDKit Wrapper for Handling Stereochemistry in Retrosynthetic Template Extraction and Application
Connor W. Coley, William H. Green, Klavs F. Jensen
Journal of Chemical Information and Modeling (2019) Vol. 59, Iss. 6, pp. 2529-2537
Open Access | Times Cited: 154
Machine learning dihydrogen activation in the chemical space surrounding Vaska's complex
Pascal Friederich, Gabriel dos Passos Gomes, Riccardo De Bin, et al.
Chemical Science (2020) Vol. 11, Iss. 18, pp. 4584-4601
Open Access | Times Cited: 148
Organic reactivity from mechanism to machine learning
Kjell Jorner, Anna Tomberg, Christoph Bauer, et al.
Nature Reviews Chemistry (2021) Vol. 5, Iss. 4, pp. 240-255
Closed Access | Times Cited: 135
Graph neural networks for automated de novo drug design
Jiacheng Xiong, Zhaoping Xiong, Kaixian Chen, et al.
Drug Discovery Today (2021) Vol. 26, Iss. 6, pp. 1382-1393
Closed Access | Times Cited: 134
Predicting Reaction Yields via Supervised Learning
A. Zuranski, Jesus I. Martinez Alvarado, Benjamin J. Shields, et al.
Accounts of Chemical Research (2021) Vol. 54, Iss. 8, pp. 1856-1865
Closed Access | Times Cited: 134
Automation and computer-assisted planning for chemical synthesis
Yuning Shen, Julia E. Borowski, Melissa A. Hardy, et al.
Nature Reviews Methods Primers (2021) Vol. 1, Iss. 1
Closed Access | Times Cited: 128
Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development
Chayna Sarkar, Biswadeep Das, Vikram Singh Rawat, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 3, pp. 2026-2026
Open Access | Times Cited: 125
Taking the leap between analytical chemistry and artificial intelligence: A tutorial review
Lucas B. Ayres, Federico J.V. Gómez, Jeb R. Linton, et al.
Analytica Chimica Acta (2021) Vol. 1161, pp. 338403-338403
Closed Access | Times Cited: 124
Chemprop: A Machine Learning Package for Chemical Property Prediction
Esther Heid, Kevin P. Greenman, Yunsie Chung, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 1, pp. 9-17
Open Access | Times Cited: 124

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