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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 26-50 of 116 citing articles:

Chemical language modeling with structured state space sequence models
Rıza Özçelik, Sarah de Ruiter, Emanuele Criscuolo, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 9
HyperPCM: Robust Task-Conditioned Modeling of Drug–Target Interactions
Emma Svensson, Pieter-Jan Hoedt, Sepp Hochreiter, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 7, pp. 2539-2553
Open Access | Times Cited: 8
Best practices for machine learning in antibody discovery and development
Leonard Wossnig, Norbert Furtmann, Andrew Buchanan, et al.
Drug Discovery Today (2024) Vol. 29, Iss. 7, pp. 104025-104025
Open Access | Times Cited: 8
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
In Silico Approach for Antibacterial Discovery: PTML Modeling of Virtual Multi-Strain Inhibitors Against Staphylococcus aureus
Valeria V. Kleandrova, M. Natália D. S. Cordeiro, M. Natália D. S. Cordeiro
Pharmaceuticals (2025) Vol. 18, Iss. 2, pp. 196-196
Open Access | Times Cited: 1
Enhancing uncertainty quantification in drug discovery with censored regression labels
Emma Svensson, Hannah Rosa Friesacher, Susanne Winiwarter, et al.
Artificial Intelligence in the Life Sciences (2025), pp. 100128-100128
Open Access | Times Cited: 1
Exploring activity landscapes with extended similarity: is Tanimoto enough?
Timothy B. Dunn, Edgar López‐López, Taewon David Kim, et al.
Molecular Informatics (2023) Vol. 42, Iss. 7
Open Access | Times Cited: 21
Harnessing the necessary nitrogen atom in chemical biology and drug discovery
Lewis D. Pennington, Philip N. Collier, Eamon Comer
Medicinal Chemistry Research (2023) Vol. 32, Iss. 7, pp. 1278-1293
Closed Access | Times Cited: 20
Large-scale prediction of activity cliffs using machine and deep learning methods of increasing complexity
Shunsuke Tamura, Tomoyuki Miyao, Jürgen Bajorath
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 17
A High-Quality Data Set of Protein–Ligand Binding Interactions Via Comparative Complex Structure Modeling
Xuelian Li, Cheng Shen, Hui Zhu, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 7, pp. 2454-2466
Closed Access | Times Cited: 7
Efficient clustering of large molecular libraries
Kenneth López Pérez, Vicky Jung, Lexin Chen, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 7
Transformers for Molecular Property Prediction: Lessons Learned from the Past Five Years
A.R. Sultan, Jochen Sieg, Miriam Mathea, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 16, pp. 6259-6280
Open Access | Times Cited: 7
Perspectives on Advancing Multimodal Learning in Environmental Science and Engineering Studies
Wenjia Liu, Jingwen Chen, Haobo Wang, et al.
Environmental Science & Technology (2024)
Closed Access | Times Cited: 6
PIGNet2: a versatile deep learning-based protein–ligand interaction prediction model for binding affinity scoring and virtual screening
Seokhyun Moon, Sang-Yeon Hwang, Jaechang Lim, et al.
Digital Discovery (2023) Vol. 3, Iss. 2, pp. 287-299
Open Access | Times Cited: 15
Applicability Domains Based on Molecular Graph Contrastive Learning Enable Graph Attention Network Models to Accurately Predict 15 Environmental End Points
Haobo Wang, Wenjia Liu, Jingwen Chen, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 44, pp. 16906-16917
Closed Access | Times Cited: 14
Data-balanced transformer for accelerated ionizable lipid nanoparticles screening in mRNA delivery
Kun Wu, Xiulong Yang, Zixu Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 5
Traversing chemical space with active deep learning for low-data drug discovery
Derek van Tilborg, Francesca Grisoni
Nature Computational Science (2024)
Closed Access | Times Cited: 5
The rise of automated curiosity-driven discoveries in chemistry
Latimah Bustillo, Teodoro Laino, Tiago Rodrigues
Chemical Science (2023) Vol. 14, Iss. 38, pp. 10378-10384
Open Access | Times Cited: 12
Enhancing antibody affinity through experimental sampling of non-deleterious CDR mutations predicted by machine learning
Thomas A. Clark, Vidya Subramanian, Akila Jayaraman, et al.
Communications Chemistry (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 11
Deep learning for low-data drug discovery: hurdles and opportunities
Derek van Tilborg, Helena Brinkmann, Emanuele Criscuolo, et al.
(2024)
Open Access | Times Cited: 4
Synergizing Chemical Structures and Bioassay Descriptions for Enhanced Molecular Property Prediction in Drug Discovery
Maximilian G. Schuh, Davide Boldini, Stephan A. Sieber
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 12, pp. 4640-4650
Open Access | Times Cited: 4
Multi‐Task ADME/PK prediction at industrial scale: leveraging large and diverse experimentaldatasets
Moritz Walter, Jens Markus Borghardt, Lina Humbeck, et al.
Molecular Informatics (2024) Vol. 43, Iss. 10
Open Access | Times Cited: 4
Multi-channel learning for integrating structural hierarchies into context-dependent molecular representation
Yue Wan, Jialu Wu, Tingjun Hou, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
StackDILI: Enhancing Drug-Induced Liver Injury Prediction through Stacking Strategy with Effective Molecular Representations
Jiahui Guan, Danhong Dong, Peilin Xie, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
The Physics-AI Dialogue in Drug Design
Pablo Andrés Vargas-Rosales, Amedeo Caflisch
RSC Medicinal Chemistry (2025)
Open Access

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