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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:

VenomPred 2.0: A Novel In Silico Platform for an Extended and Human Interpretable Toxicological Profiling of Small Molecules
Miriana Di Stefano, Salvatore Galati, L Piazza, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 7, pp. 2275-2289
Open Access | Times Cited: 19

Showing 19 citing articles:

Machine Learning‐Enabled Drug‐Induced Toxicity Prediction
Changsen Bai, Lianlian Wu, Ruijiang Li, et al.
Advanced Science (2025)
Open Access | Times Cited: 1
Chemical Space Networks Enhance Toxicity Recognition via Graph Embedding
Fabrizio Mastrolorito, Nicola Gambacorta, Fulvio Ciriaco, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access | Times Cited: 1
Applied Artificial Intelligence in Materials Science and Material Design
Emigdio Chávez‐Ángel, Martin Eriksen, Alejandro Castro‐Álvarez, et al.
Advanced Intelligent Systems (2025)
Open Access | Times Cited: 1
Editorial: Machine Learning in Bio-cheminformatics
Kenneth M. Merz, Guo‐Wei Wei, Feng Zhu
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 7, pp. 2125-2128
Closed Access | Times Cited: 5
Machine Learning for Toxicity Prediction Using Chemical Structures: Pillars for Success in the Real World
Srijit Seal, Manas Mahale, Miguel García-Ortegón, et al.
Chemical Research in Toxicology (2025)
Open Access
Where developmental toxicity meets explainable artificial intelligence: state-of-the-art and perspectives
Maria Vittoria Togo, Fabrizio Mastrolorito, Angelica Orfino, et al.
Expert Opinion on Drug Metabolism & Toxicology (2023) Vol. 20, Iss. 7, pp. 561-577
Closed Access | Times Cited: 10
A series of benzensulfonamide derivatives as new potent carbonic anhydrase IX and XII inhibitors
Susanna Nencetti, Doretta Cuffaro, Lidia Ciccone, et al.
Future Medicinal Chemistry (2025), pp. 1-15
Closed Access
SynthMol: A Drug Safety Prediction Framework Integrating Graph Attention and Molecular Descriptors into Pre-Trained Geometric Models
Zidong Su, Rong Zhang, Xiaoyu Fan, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
10-methoxy-leonurine accelerated wound healing through ErbB4/PI3K-AKT pathway
Yue Zhang, Bang-Yin Tan, Hui Peng, et al.
Journal of Ethnopharmacology (2025), pp. 119641-119641
Closed Access
AQUA Tox: A web tool for predicting aquatic toxicity in rotifer species using intrinsic explainable models
Karel Diéguez‐Santana, Gerardo M. Casañola‐Martín, Roldan Torres-Gutiérrez, et al.
Journal of Hazardous Materials (2025), pp. 138050-138050
Closed Access
Blood biochemical landscape and new insights into clinical decision-making for polycystic ovary syndrome in Chinese women: a prospective cohort study
Yutong Li, Xiufeng Lin, Ke Zou, et al.
Frontiers in Endocrinology (2025) Vol. 16
Open Access
Astragalus polysaccharides inhibits tumor proliferation and enhances cisplatin sensitivity in bladder cancer by regulating the PI3K/AKT/FoxO1 axis
Ruiqi Chen, Yutong Li, Ling Zuo, et al.
International Journal of Biological Macromolecules (2025), pp. 143739-143739
Closed Access
Fate-tox: fragment attention transformer for E(3)-equivariant multi-organ toxicity prediction
Sy Ha, Dongmin Bang, Sun Yeou Kim
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access
Unlocking the potential of AI: Machine learning and deep learning models for predicting carcinogenicity of chemicals
Wenjing Guo, Jie Liu, Fan Dong, et al.
Journal of Environmental Science and Health Part C (2024), pp. 1-28
Closed Access | Times Cited: 3
Data-driven toxicity prediction in drug discovery: Current status and future directions
Ningning Wang, Xinliang David Li, Jing Xiao, et al.
Drug Discovery Today (2024), pp. 104195-104195
Closed Access | Times Cited: 3
Design, synthesis and biological evaluation of arylsulfonamides as ADAMTS7 inhibitors
Doretta Cuffaro, Tina Burkhard, Bianca Laura Bernardoni, et al.
RSC Medicinal Chemistry (2024) Vol. 15, Iss. 8, pp. 2806-2825
Open Access | Times Cited: 1
Towards novel small-molecule inhibitors blocking PD-1/PD-L1 pathway: From explainable machine learning models to molecular dynamics simulation
Xiaoyan Wu, Jingyi Liang, Luming Meng, et al.
International Journal of Biological Macromolecules (2024), pp. 136325-136325
Closed Access | Times Cited: 1
Identification of New GSK3β Inhibitors through a Consensus Machine Learning-Based Virtual Screening
Salvatore Galati, Miriana Di Stefano, Simone Bertini, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 24, pp. 17233-17233
Open Access | Times Cited: 3
Discovery and Development of Promising Anticancer Agents via Computational and Experimental
Simone Carradori
Anti-Cancer Agents in Medicinal Chemistry (2024) Vol. 24, Iss. 4, pp. 235-235
Closed Access
AISMPred: A Machine Learning Approach for Predicting Anti-Inflammatory Small Molecules
Subathra Selvam, Priya Dharshini Balaji, Honglae Sohn, et al.
Pharmaceuticals (2024) Vol. 17, Iss. 12, pp. 1693-1693
Open Access
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