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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:

Model agnostic generation of counterfactual explanations for molecules
Geemi P. Wellawatte, Aditi Seshadri, Andrew Dickson White
Chemical Science (2022) Vol. 13, Iss. 13, pp. 3697-3705
Open Access | Times Cited: 95

Showing 1-25 of 95 citing articles:

On scientific understanding with artificial intelligence
Mario Krenn, Robert Pollice, Si Yue Guo, et al.
Nature Reviews Physics (2022) Vol. 4, Iss. 12, pp. 761-769
Open Access | Times Cited: 219
SELFIES and the future of molecular string representations
Mario Krenn, Qianxiang Ai, Senja Barthel, et al.
Patterns (2022) Vol. 3, Iss. 10, pp. 100588-100588
Open Access | Times Cited: 155
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: 131
A Survey of Algorithmic Recourse: Contrastive Explanations and Consequential Recommendations
Amir-Hossein Karimi, Gilles Barthe, Bernhard Schölkopf, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 5, pp. 1-29
Open Access | Times Cited: 81
Scoring Functions for Protein-Ligand Binding Affinity Prediction Using Structure-based Deep Learning: A Review
Rocco Meli, Garrett M. Morris, Philip C. Biggin
Frontiers in Bioinformatics (2022) Vol. 2
Open Access | Times Cited: 77
Chemistry-intuitive explanation of graph neural networks for molecular property prediction with substructure masking
Zhenhua Wu, Jike Wang, Hongyan Du, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 71
Data-Driven Design of Polymer-Based Biomaterials: High-throughput Simulation, Experimentation, and Machine Learning
Roshan Patel, Michael Webb
ACS Applied Bio Materials (2023) Vol. 7, Iss. 2, pp. 510-527
Closed Access | Times Cited: 51
A Perspective on Explanations of Molecular Prediction Models
Geemi P. Wellawatte, Heta A. Gandhi, Aditi Seshadri, et al.
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 8, pp. 2149-2160
Open Access | Times Cited: 48
Accurate clinical toxicity prediction using multi-task deep neural nets and contrastive molecular explanations
Bhanushee Sharma, Vijil Chenthamarakshan, Amit Dhurandhar, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 47
Recent Advances in Machine-Learning-Based Chemoinformatics: A Comprehensive Review
Sarfaraz K. Niazi, Zamara Mariam
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 14, pp. 11488-11488
Open Access | Times Cited: 44
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
Sahil Verma, Varich Boonsanong, Minh Hoang, et al.
ACM Computing Surveys (2024) Vol. 56, Iss. 12, pp. 1-42
Open Access | Times Cited: 34
AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery
Yue Xu, Shihao Ma, Haotian Cui, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 23
Active learning of the thermodynamics-dynamics trade-off in protein condensates
Yaxin An, Michael Webb, William M. Jacobs
Science Advances (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 22
Invalid SMILES are beneficial rather than detrimental to chemical language models
Michael A. Skinnider
Nature Machine Intelligence (2024) Vol. 6, Iss. 4, pp. 437-448
Open Access | Times Cited: 17
Artificial design of organic emitters via a genetic algorithm enhanced by a deep neural network
AkshatKumar Nigam, Robert Pollice, Pascal Friederich, et al.
Chemical Science (2024) Vol. 15, Iss. 7, pp. 2618-2639
Open Access | Times Cited: 16
Quantitative evaluation of explainable graph neural networks for molecular property prediction
Jiahua Rao, Shuangjia Zheng, Yutong Lu, et al.
Patterns (2022) Vol. 3, Iss. 12, pp. 100628-100628
Open Access | Times Cited: 47
Group SELFIES: a robust fragment-based molecular string representation
Austin H. Cheng, Andy Cai, Santiago Miret, et al.
Digital Discovery (2023) Vol. 2, Iss. 3, pp. 748-758
Open Access | Times Cited: 31
Open-Source Machine Learning in Computational Chemistry
Alexander Hagg, Karl N. Kirschner
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 15, pp. 4505-4532
Open Access | Times Cited: 28
What is missing in autonomous discovery: open challenges for the community
Phillip M. Maffettone, Pascal Friederich, Sterling G. Baird, et al.
Digital Discovery (2023) Vol. 2, Iss. 6, pp. 1644-1659
Open Access | Times Cited: 26
Differences in learning characteristics between support vector machine and random forest models for compound classification revealed by Shapley value analysis
Friederike Maite Siemers, Jürgen Bajorath
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 23
Deep learning metal complex properties with natural quantum graphs
Hannes Kneiding, Ruslan Lukin, Lucas Lang, et al.
Digital Discovery (2023) Vol. 2, Iss. 3, pp. 618-633
Open Access | Times Cited: 22
Identifying Substructures That Facilitate Compounds to Penetrate the Blood–Brain Barrier via Passive Transport Using Machine Learning Explainer Models
Lucca Caiaffa Santos Rosa, Caio Oliveira Argolo, Cayque Monteiro Castro Nascimento, et al.
ACS Chemical Neuroscience (2024) Vol. 15, Iss. 11, pp. 2144-2159
Open Access | Times Cited: 8
Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation
Karthik Raman, Rukmini Kumar, Cynthia J. Musante, et al.
Clinical and Translational Science (2025) Vol. 18, Iss. 1
Open Access | Times Cited: 1
Chemical space as a unifying theme for chemistry
Jean‐Louis Reymond
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access | Times Cited: 1
Counterfactual Learning on Graphs: A Survey
Zhimeng Guo, Zongyu Wu, Teng Xiao, et al.
Deleted Journal (2025) Vol. 22, Iss. 1, pp. 17-59
Open Access | Times Cited: 1
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