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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:

Exposing the Limitations of Molecular Machine Learning with Activity Cliffs
Derek van Tilborg, Alisa Alenicheva, Francesca Grisoni
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 23, pp. 5938-5951
Open Access | Times Cited: 116

Showing 51-75 of 116 citing articles:

InterDIA: Interpretable Prediction of Drug-induced Autoimmunity through Ensemble Machine Learning Approaches
Lina Huang, P. L. Liu, Xiaojie Huang
Toxicology (2025), pp. 154064-154064
Closed Access
Identification and optimization of a small molecule inhibitor of the ovarian tumor protease of the Crimean-Congo hemorrhagic fever virus
Lorenz Beckmann, Fabian Ließmann, Maik Icker, et al.
Bioorganic & Medicinal Chemistry (2025), pp. 118093-118093
Closed Access
Web Server-based Deep Learning-Driven Predictive Models for Respiratory Toxicity of Environmental Chemicals: Mechanistic Insights and Interpretability
Na Li, Zhaoyang Chen, Wenhui Zhang, et al.
Journal of Hazardous Materials (2025) Vol. 489, pp. 137575-137575
Closed Access
Establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features
You Wu, Ke Tang, Chunzheng Wang, et al.
Acta Pharmaceutica Sinica B (2025)
Open Access
The European Federation for Medicinal Chemistry and Chemical Biology (EFMC) Best Practice Initiative: Hit to Lead
Jean Quancard, Anders Bach, Chiara Borsari, et al.
ChemMedChem (2025)
Closed Access
A small-scale data driven and graph neural network based toxicity prediction method of compounds
Xin Zhao, Shuyi Zhang, Tao Zhang, et al.
Computational Biology and Chemistry (2025) Vol. 117, pp. 108393-108393
Closed Access
A database for large-scale docking and experimental results
Brendan W. Hall, Tia A. Tummino, Khanh Tang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
MultiCycPermea: accurate and interpretable prediction of cyclic peptide permeability using a multimodal image-sequence model
Zixu Wang, Yangyang Chen, Yifan Shang, et al.
BMC Biology (2025) Vol. 23, Iss. 1
Open Access
From NMR to AI: Do We Need 1H NMR Experimental Spectra to Obtain High-Quality logD Prediction Models?
Arkadiusz Leniak, Wojciech Pietruś, Aleksandra Świderska, et al.
Journal of Chemical Information and Modeling (2025)
Open Access
Achieving well-informed decision-making in drug discovery: a comprehensive calibration study using neural network-based structure-activity models
Hannah Rosa Friesacher, Ola Engkvist, Lewis Mervin, et al.
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access
A data-driven generative strategy to avoid reward hacking in multi-objective molecular design
Tatsuya Yoshizawa, Shoichi Ishida, Tomohiro Sato, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
BitBIRCH: Efficient clustering of large molecular libraries
Kenneth López Pérez, Vicky Jung, Lexin Chen, et al.
Digital Discovery (2025)
Open Access
iCliff Taylor's version: Robust and Efficient Activity Cliff Determination
Kenneth López-Pérez, Ramón Alain Miranda‐Quintana
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Leveraging Transfer Learning for Predicting Protein–Small-Molecule Interaction Predictions
Jian Wang, Nikolay V. Dokholyan
Journal of Chemical Information and Modeling (2025)
Closed Access
Development of an Interpretable QSAR Model for Predicting Acute Oral Toxicity of Organophosphates in Rats Based on GA-MLR Algorithm
Guanlong Yu, Qianlan Zhuo, Chuan Wang
Journal of Environmental Science and Health Part B (2025), pp. 1-13
Closed Access
Activity cliff-aware reinforcement learning for de novo drug design
Xiuyuan Hu, Guoqing Liu, Yang Zhao, et al.
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access
ACtriplet: An improved deep learning model for activity cliffs prediction by integrating triplet loss and pre-training
Xinxin Yu, Yimeng Wang, Long Chen, et al.
Journal of Pharmaceutical Analysis (2025), pp. 101317-101317
Open Access
A Database for Large-Scale Docking and Experimental Results
Brendan W. Hall, Tia A. Tummino, Khanh Tang, et al.
Journal of Chemical Information and Modeling (2025)
Open Access
Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry
Austin M. Mroz, Annabel R. Basford, Friedrich Hastedt, et al.
Chemical Society Reviews (2025)
Open Access
Evaluating Scalable Supervised Learning for Synthesize-on-Demand Chemical Libraries
Moayad Alnammi, Shengchao Liu, Spencer S. Ericksen, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 17, pp. 5513-5528
Open Access | Times Cited: 9
Recent Advances in Toxicity Prediction: Applications of Deep Graph Learning
Yuwei Miao, Hehuan Ma, Junzhou Huang
Chemical Research in Toxicology (2023) Vol. 36, Iss. 8, pp. 1206-1226
Closed Access | Times Cited: 8
Unlocking the Potential of Clustering and Classification Approaches: Navigating Supervised and Unsupervised Chemical Similarity
Kamel Mansouri, Kyla W. Taylor, Scott S. Auerbach, et al.
Environmental Health Perspectives (2024) Vol. 132, Iss. 8
Open Access | Times Cited: 2
A physics-inspired approach to the understanding of molecular representations and models
Luke Dicks, David Graff, Kirk E. Jordan, et al.
Molecular Systems Design & Engineering (2024) Vol. 9, Iss. 5, pp. 449-455
Open Access | Times Cited: 2
Uncovering and tackling fundamental limitations of compound potency predictions using machine learning models
Tiago Janela, Jürgen Bajorath
Cell Reports Physical Science (2024) Vol. 5, Iss. 6, pp. 101988-101988
Open Access | Times Cited: 2
Unsupervised manifold embedding to encode molecular quantum information for supervised learning of chemical data
Tonglei Li, Nicholas J. Huls, Shan Lu, et al.
Communications Chemistry (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 2

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