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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:

QSAR without borders
Eugene Muratov, Jürgen Bajorath, Robert P. Sheridan, et al.
Chemical Society Reviews (2020) Vol. 49, Iss. 11, pp. 3525-3564
Open Access | Times Cited: 591

Showing 1-25 of 591 citing articles:

Drug discovery with explainable artificial intelligence
José Jiménez-Luna, Francesca Grisoni, Gisbert Schneider
Nature Machine Intelligence (2020) Vol. 2, Iss. 10, pp. 573-584
Open Access | Times Cited: 686
Machine learning for alloys
Gus L. W. Hart, Tim Mueller, Cormac Toher, et al.
Nature Reviews Materials (2021) Vol. 6, Iss. 8, pp. 730-755
Closed Access | Times Cited: 405
Zwitterionic Biomaterials
Qingsi Li, Chiyu Wen, Jing Yang, et al.
Chemical Reviews (2022) Vol. 122, Iss. 23, pp. 17073-17154
Closed Access | Times Cited: 321
State-of-the-art augmented NLP transformer models for direct and single-step retrosynthesis
Igor V. Tetko, Pavel Karpov, Ruud van Deursen, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 296
Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery
Haoxin Mai, Tu C. Le, Dehong Chen, et al.
Chemical Reviews (2022) Vol. 122, Iss. 16, pp. 13478-13515
Closed Access | Times Cited: 236
Advances in De Novo Drug Design: From Conventional to Machine Learning Methods
Varnavas D. Mouchlis, Antreas Afantitis, Angela Serra, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 4, pp. 1676-1676
Open Access | Times Cited: 229
Machine learning the ropes: principles, applications and directions in synthetic chemistry
Felix Strieth‐Kalthoff, Frederik Sandfort, Marwin Segler, et al.
Chemical Society Reviews (2020) Vol. 49, Iss. 17, pp. 6154-6168
Closed Access | Times Cited: 215
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
Lior Hirschfeld, Kyle Swanson, Kevin Yang, et al.
Journal of Chemical Information and Modeling (2020) Vol. 60, Iss. 8, pp. 3770-3780
Open Access | Times Cited: 209
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: 175
A critical overview of computational approaches employed for COVID-19 drug discovery
Eugene Muratov, Rommie E. Amaro, Carolina Horta Andrade, et al.
Chemical Society Reviews (2021) Vol. 50, Iss. 16, pp. 9121-9151
Open Access | Times Cited: 169
Artificial Intelligence in Chemistry: Current Trends and Future Directions
Zachary J. Baum, Xiang Yu, Philippe Y. Ayala, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 7, pp. 3197-3212
Closed Access | Times Cited: 162
Discovery of a structural class of antibiotics with explainable deep learning
Felix Wong, Erica J. Zheng, Jacqueline A. Valeri, et al.
Nature (2023) Vol. 626, Iss. 7997, pp. 177-185
Open Access | Times Cited: 144
Machine Learning for Chemical Reactivity: The Importance of Failed Experiments
Felix Strieth‐Kalthoff, Frederik Sandfort, Marius Kühnemund, et al.
Angewandte Chemie International Edition (2022) Vol. 61, Iss. 29
Closed Access | Times Cited: 140
Sorption-enhanced Steam Methane Reforming for Combined CO2 Capture and Hydrogen Production: A State-of-the-Art Review
Salman Masoudi Soltani, Abhishek Lahiri, Husain Bahzad, et al.
Carbon Capture Science & Technology (2021) Vol. 1, pp. 100003-100003
Open Access | Times Cited: 137
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
Machine learning meets mechanistic modelling for accurate prediction of experimental activation energies
Kjell Jorner, Tore Brinck, Per‐Ola Norrby, et al.
Chemical Science (2020) Vol. 12, Iss. 3, pp. 1163-1175
Open 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
Evidential Deep Learning for Guided Molecular Property Prediction and Discovery
Ava P. Soleimany, Alexander Amini, Samuel Goldman, et al.
ACS Central Science (2021) Vol. 7, Iss. 8, pp. 1356-1367
Open Access | Times Cited: 133
Natural product drug discovery in the artificial intelligence era
Fernanda I. Saldívar‐González, Victor Daniel Aldas-Bulos, José L. Medina‐Franco, et al.
Chemical Science (2021) Vol. 13, Iss. 6, pp. 1526-1546
Open Access | Times Cited: 129
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: 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
Bioactive Synthetic Polymers
Kenward Jung, Nathaniel Corrigan, Edgar H. H. Wong, et al.
Advanced Materials (2021) Vol. 34, Iss. 2
Closed Access | Times Cited: 100
Artificial intelligence in drug discovery: applications and techniques
Jianyuan Deng, Zhibo Yang, Iwao Ojima, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 98
Structure-Based Virtual Screening for Ligands of G Protein–Coupled Receptors: What Can Molecular Docking Do for You?
Flavio Ballante, Albert J. Kooistra, Stefanie Kampen, et al.
Pharmacological Reviews (2021) Vol. 73, Iss. 4, pp. 1698-1736
Open Access | Times Cited: 98
FP-GNN: a versatile deep learning architecture for enhanced molecular property prediction
Hanxuan Cai, Huimin Zhang, Duancheng Zhao, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Open Access | Times Cited: 90
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