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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:

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: 163

Showing 1-25 of 163 citing articles:

ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support
Li Fu, Shaohua Shi, Jiacai Yi, et al.
Nucleic Acids Research (2024) Vol. 52, Iss. W1, pp. W422-W431
Open Access | Times Cited: 173
Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting
David Buterez, Jon Paul Janet, Steven J. Kiddle, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 22
Machine Learning-Assisted High-Donor-Number Electrolyte Additive Screening toward Construction of Dendrite-Free Aqueous Zinc-Ion Batteries
Haoran Luo, Qianzhi Gou, Yu Zheng, et al.
ACS Nano (2025)
Closed Access | Times Cited: 5
Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates
Yunsie Chung, William H. Green
Chemical Science (2024) Vol. 15, Iss. 7, pp. 2410-2424
Open Access | Times Cited: 14
Benchmarking Active Learning Protocols for Ligand-Binding Affinity Prediction
Rohan Gorantla, Alžbeta Kubincová, Benjamin S. Suutari, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 6, pp. 1955-1965
Open Access | Times Cited: 14
Machine learning for the advancement of membrane science and technology: A critical review
Gergő Ignácz, Lana Bader, Aron K. Beke, et al.
Journal of Membrane Science (2024) Vol. 713, pp. 123256-123256
Open Access | Times Cited: 12
Quantum mechanical-based strategies in drug discovery: Finding the pace to new challenges in drug design
Tiziana Ginex, Javier Vázquez, Carolina Estarellas, et al.
Current Opinion in Structural Biology (2024) Vol. 87, pp. 102870-102870
Open Access | Times Cited: 11
Artificial intelligence-guided design of lipid nanoparticles for pulmonary gene therapy
Jacob Witten, Idris O. Raji, Rajith S. Manan, et al.
Nature Biotechnology (2024)
Closed Access | Times Cited: 11
When Do Quantum Mechanical Descriptors Help Graph Neural Networks to Predict Chemical Properties?
Shih‐Cheng Li, Haoyang Wu, Angiras Menon, et al.
Journal of the American Chemical Society (2024) Vol. 146, Iss. 33, pp. 23103-23120
Closed Access | Times Cited: 10
Will we ever be able to accurately predict solubility?
Pierre Llompart, Claire Minoletti, Shamkhal Baybekov, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 9
Calibration-free reaction yield quantification by HPLC with a machine-learning model of extinction coefficients
Matthew A. McDonald, Brent A. Koscher, Richard B. Canty, et al.
Chemical Science (2024) Vol. 15, Iss. 26, pp. 10092-10100
Open Access | Times Cited: 9
ADMET evaluation in drug discovery: 21. Application and industrial validation of machine learning algorithms for Caco-2 permeability prediction
Dong Wang, Jieyu Jin, Guqin Shi, et al.
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access | Times Cited: 1
CatPred: a comprehensive framework for deep learning in vitro enzyme kinetic parameters
Veda Sheersh Boorla, Costas D. Maranas
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 1
Multimodal fused deep learning for drug property prediction: Integrating chemical language and molecular graph
Xiaohua Lu, Liangxu Xie, Lei Xu, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 1666-1679
Open Access | Times Cited: 8
Performance and robustness of small molecule retention time prediction with molecular graph neural networks in industrial drug discovery campaigns
Daniel Vik, David Pii, Chirag Mudaliar, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Thermodynamics-consistent graph neural networks
Jan G. Rittig, Alexander Mitsos
Chemical Science (2024)
Open Access | Times Cited: 7
High-throughput quantum theory of atoms in molecules (QTAIM) for geometric deep learning of molecular and reaction properties
Santiago Vargas, Winston Gee, Anastassia N. Alexandrova
Digital Discovery (2024) Vol. 3, Iss. 5, pp. 987-998
Open Access | Times Cited: 6
Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules
Davide Bassani, Neil Parrott, Nenad Manevski, et al.
Expert Opinion on Drug Discovery (2024) Vol. 19, Iss. 6, pp. 683-698
Open Access | Times Cited: 6
ROBERT: Bridging the Gap Between Machine Learning and Chemistry
David Dalmau, Juan V. Alegre‐Requena
Wiley Interdisciplinary Reviews Computational Molecular Science (2024) Vol. 14, Iss. 5
Open Access | Times Cited: 6
Machine-Learning-Assisted Design of Buried-Interface Engineering Materials for High-Efficiency and Stable Perovskite Solar Cells
Qi Zhang, Han Wang, Qiangqiang Zhao, et al.
ACS Energy Letters (2024), pp. 5924-5934
Closed Access | Times Cited: 6
Assessment of Fine-Tuned Large Language Models for Real-World Chemistry and Material Science Applications
Joren Van Herck, M.V. Gil, Kevin Maik Jablonka, et al.
Chemical Science (2024)
Open Access | Times Cited: 6
A hybrid modelling approach to compare chemical separation technologies in terms of energy consumption and carbon dioxide emissions
Gergő Ignácz, Aron K. Beke, Viktor Tóth, et al.
Nature Energy (2024)
Open Access | Times Cited: 6
CPSign: conformal prediction for cheminformatics modeling
Staffan Arvidsson, Ulf Norinder, Jonathan Alvarsson, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 5
Deep learning pipeline for accelerating virtual screening in drug discovery
Fatima Noor, Muhammad Junaid, Atiah H. Almalki, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
EnzymeMap: curation, validation and data-driven prediction of enzymatic reactions
Esther Heid, Daniel Probst, William H. Green, et al.
Chemical Science (2023) Vol. 14, Iss. 48, pp. 14229-14242
Open Access | Times Cited: 12
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