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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:

Transfer learning enables the molecular transformer to predict regio- and stereoselective reactions on carbohydrates
Giorgio Pesciullesi, Philippe Schwaller, Teodoro Laino, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 194

Showing 1-25 of 194 citing articles:

Scientific discovery in the age of artificial intelligence
Hanchen Wang, Tianfan Fu, Yuanqi Du, et al.
Nature (2023) Vol. 620, Iss. 7972, pp. 47-60
Closed Access | Times Cited: 582
Geometric deep learning on molecular representations
Kenneth Atz, Francesca Grisoni, Gisbert Schneider
Nature Machine Intelligence (2021) Vol. 3, Iss. 12, pp. 1023-1032
Closed Access | Times Cited: 229
Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development
Arash Keshavarzi Arshadi, Julia Webb, Milad Salem, et al.
Frontiers in Artificial Intelligence (2020) Vol. 3
Open Access | Times Cited: 209
Machine Learning in Chemical Engineering: Strengths, Weaknesses, Opportunities, and Threats
Maarten R. Dobbelaere, Pieter Plehiers, Ruben Van de Vijver, et al.
Engineering (2021) Vol. 7, Iss. 9, pp. 1201-1211
Open Access | Times Cited: 190
Prediction of chemical reaction yields using deep learning
Philippe Schwaller, Alain C. Vaucher, Teodoro Laino, et al.
Machine Learning Science and Technology (2021) Vol. 2, Iss. 1, pp. 015016-015016
Open Access | Times Cited: 165
Machine Learning May Sometimes Simply Capture Literature Popularity Trends: A Case Study of Heterocyclic Suzuki–Miyaura Coupling
Wiktor Beker, Rafał Roszak, Agnieszka Wołos, et al.
Journal of the American Chemical Society (2022) Vol. 144, Iss. 11, pp. 4819-4827
Open Access | Times Cited: 135
Chemformer: a pre-trained transformer for computational chemistry
Ross Irwin, Spyridon Dimitriadis, Jiazhen He, et al.
Machine Learning Science and Technology (2021) Vol. 3, Iss. 1, pp. 015022-015022
Open Access | Times Cited: 123
Ab Initio Machine Learning in Chemical Compound Space
Bing Huang, O. Anatole von Lilienfeld
Chemical Reviews (2021) Vol. 121, Iss. 16, pp. 10001-10036
Open Access | Times Cited: 121
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits
Mikołaj Sacha, Mikołaj Błaż, Piotr Byrski, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 7, pp. 3273-3284
Open Access | Times Cited: 109
Real-time personalized health status prediction of lithium-ion batteries using deep transfer learning
Guijun Ma, Songpei Xu, Benben Jiang, et al.
Energy & Environmental Science (2022) Vol. 15, Iss. 10, pp. 4083-4094
Open Access | Times Cited: 95
Evaluation guidelines for machine learning tools in the chemical sciences
Andreas Bender, Nadine Schneider, Marwin Segler, et al.
Nature Reviews Chemistry (2022) Vol. 6, Iss. 6, pp. 428-442
Closed Access | Times Cited: 95
Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 5, pp. 525-535
Open Access | Times Cited: 94
Biocatalysed synthesis planning using data-driven learning
Daniel Probst, Matteo Manica, Yves Gaëtan Nana Teukam, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 89
Machine intelligence for chemical reaction space
Philippe Schwaller, Alain C. Vaucher, Rubén Laplaza, et al.
Wiley Interdisciplinary Reviews Computational Molecular Science (2022) Vol. 12, Iss. 5
Open Access | Times Cited: 87
Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP
Shuangjia Zheng, Tao Zeng, Chengtao Li, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 74
Retrosynthetic reaction pathway prediction through neural machine translation of atomic environments
Umit Volkan Ucak, Islambek Ashyrmamatov, Junsu Ko, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 69
Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
Zhengkai Tu, Thijs Stuyver, Connor W. Coley
Chemical Science (2022) Vol. 14, Iss. 2, pp. 226-244
Open Access | Times Cited: 66
Machine learning-enabled retrobiosynthesis of molecules
Tianhao Yu, Aashutosh Girish Boob, Michael Volk, et al.
Nature Catalysis (2023) Vol. 6, Iss. 2, pp. 137-151
Closed Access | Times Cited: 61
On the use of real-world datasets for reaction yield prediction
Mandana Saebi, Bozhao Nan, John E. Herr, et al.
Chemical Science (2023) Vol. 14, Iss. 19, pp. 4997-5005
Open Access | Times Cited: 59
Exploring the Intersection of Artificial Intelligence and Clinical Healthcare: A Multidisciplinary Review
Celina Silvia Stafie, Irina-Georgeta Șufaru, Cristina Mihaela Ghiciuc, et al.
Diagnostics (2023) Vol. 13, Iss. 12, pp. 1995-1995
Open Access | Times Cited: 45
Accelerated chemical science with AI
Seoin Back, Alán Aspuru-Guzik, Michele Ceriotti, et al.
Digital Discovery (2023) Vol. 3, Iss. 1, pp. 23-33
Open Access | Times Cited: 36
Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptors
Yanfei Guan, Connor W. Coley, Haoyang Wu, et al.
Chemical Science (2020) Vol. 12, Iss. 6, pp. 2198-2208
Open Access | Times Cited: 101
An effective self-supervised framework for learning expressive molecular global representations to drug discovery
Pengyong Li, Jun Wang, Yixuan Qiao, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 96
Concepts and applications of chemical fingerprint for hit and lead screening
Jingbo Yang, Yiyang Cai, Kairui Zhao, et al.
Drug Discovery Today (2022) Vol. 27, Iss. 11, pp. 103356-103356
Closed Access | Times Cited: 61
Predicting enzymatic reactions with a molecular transformer
David Kreutter, Philippe Schwaller, Jean‐Louis Reymond
Chemical Science (2021) Vol. 12, Iss. 25, pp. 8648-8659
Open Access | Times Cited: 60
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