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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:

Generative deep learning enables the discovery of a potent and selective RIPK1 inhibitor
Yueshan Li, Liting Zhang, Yifei Wang, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

Artificial Intelligence and Machine Learning in Pharmacological Research: Bridging the Gap Between Data and Drug Discovery
Shruti Singh, Rajesh Kumar, Shuvasree Payra, et al.
Cureus (2023)
Open Access | Times Cited: 70
PocketFlow is a data-and-knowledge-driven structure-based molecular generative model
Yuanyuan Jiang, Guo Zhang, Jing You, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 3, pp. 326-337
Open Access | Times Cited: 30
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: 18
Artificial intelligence in drug development
Kang Zhang, Xin Yang, Yifei Wang, et al.
Nature Medicine (2025) Vol. 31, Iss. 1, pp. 45-59
Closed Access | Times Cited: 17
Deep Generative Models in De Novo Drug Molecule Generation
Chao Pang, Jianbo Qiao, Xiangxiang Zeng, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 7, pp. 2174-2194
Closed Access | Times Cited: 35
The Hitchhiker’s Guide to Deep Learning Driven Generative Chemistry
Yan A. Ivanenkov, Bogdan Zagribelnyy, А. В. Малышев, et al.
ACS Medicinal Chemistry Letters (2023) Vol. 14, Iss. 7, pp. 901-915
Open Access | Times Cited: 25
The Artificial Intelligence-Driven Pharmaceutical Industry: A Paradigm Shift in Drug Discovery, Formulation Development, Manufacturing, Quality Control, and Post-Market Surveillance
Kampanart Huanbutta, Kanokporn Burapapadh, Pakorn Kraisit, et al.
European Journal of Pharmaceutical Sciences (2024) Vol. 203, pp. 106938-106938
Open Access | Times Cited: 12
Sample efficient reinforcement learning with active learning for molecular design
Michael Dodds, Jeff Guo, Thomas Löhr, et al.
Chemical Science (2024) Vol. 15, Iss. 11, pp. 4146-4160
Open Access | Times Cited: 11
Practical Three-Component Regioselective Synthesis of Drug-Like 3-Aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnolines as Potential Non-Covalent Multi-Targeting Inhibitors To Combat Neurodegenerative Diseases
Hossein Mousavi, Mehdi Rimaz, Behzad Zeynizadeh
ACS Chemical Neuroscience (2024) Vol. 15, Iss. 9, pp. 1828-1881
Closed Access | Times Cited: 9
Image-based generation for molecule design with SketchMol
Zixu Wang, Yangyang Chen, Pengsen Ma, et al.
Nature Machine Intelligence (2025)
Closed Access | Times Cited: 1
Machine learning-based optimal design of an acoustic black hole metaplate for enhanced bandgap and load-bearing capacity
Sihao Han, Nanfang Ma, Qiang Han, et al.
Mechanical Systems and Signal Processing (2024) Vol. 215, pp. 111436-111436
Closed Access | Times Cited: 8
AutoMolDesigner for Antibiotic Discovery: An AI-Based Open-Source Software for Automated Design of Small-Molecule Antibiotics
Tao Shen, Jiale Guo, Zunsheng Han, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 3, pp. 575-583
Open Access | Times Cited: 7
Unlocking the Potential of Generative Artificial Intelligence in Drug Discovery
Virgilio Romanelli, Carmen Cerchia, Antonio Lavecchia
Springer eBooks (2024), pp. 37-63
Closed Access | Times Cited: 7
Transient receptor potential ankyrin 1 (TRPA1) modulators: Recent update and future perspective
Zelin Hu, Ya Zhang, Wenhan Yu, et al.
European Journal of Medicinal Chemistry (2023) Vol. 257, pp. 115392-115392
Closed Access | Times Cited: 16
Artificial intelligence in molecular de novo design: Integration with experiment
Jon Paul Janet, Lewis Mervin, Ola Engkvist
Current Opinion in Structural Biology (2023) Vol. 80, pp. 102575-102575
Open Access | Times Cited: 14
Structure-Based Drug Design with a Deep Hierarchical Generative Model
Jesse A. Weller, Remo Rohs
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 16, pp. 6450-6463
Open Access | Times Cited: 6
De Novo Generation and Identification of Novel Compounds with Drug Efficacy Based on Machine Learning
Dakuo He, Qing Liu, Yan Mi, et al.
Advanced Science (2024) Vol. 11, Iss. 11
Open Access | Times Cited: 5
Receptor-interacting protein kinase 1 (RIPK1) inhibitor: a review of the patent literature (2018-present)
Lijuan Xu, Wannian Zhang, Chunlin Zhuang
Expert Opinion on Therapeutic Patents (2023) Vol. 33, Iss. 2, pp. 101-124
Closed Access | Times Cited: 11
Accelerating drug discovery, development, and clinical trials by artificial intelligence
Yilun Zhang, Mohamed Mastouri, Yang Zhang
Med (2024) Vol. 5, Iss. 9, pp. 1050-1070
Closed Access | Times Cited: 4
Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation
Yan Sun, Jiajing Wu, Beilei Shen, et al.
International Journal of Molecular Sciences (2025) Vol. 26, Iss. 3, pp. 1381-1381
Open Access
Multi-Criteria Decision Analysis in Drug Discovery
Rafał A. Bachorz, Michael S. Lawless, David W. Miller, et al.
Applied Biosciences (2025) Vol. 4, Iss. 1, pp. 2-2
Open Access
Deep lead optimization enveloped in protein pocket and its application in designing potent and selective ligands targeting LTK protein
S Y Chen, Odin Zhang, Chenran Jiang, et al.
Nature Machine Intelligence (2025)
Closed Access
DTF-diffusion: A 3D equivariant diffusion generation model based on ligand-target information fusion
Jianxin Wang, Yongxin Zhu, Yushuang Liu, et al.
Computational Biology and Chemistry (2025) Vol. 117, pp. 108392-108392
Closed Access
Accelerating discovery of bioactive ligands with pharmacophore-informed generative models
Weixin Xie, Jianhang Zhang, Qin Xie, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools
Varun Dewaker, Vivek Kumar Morya, Yeon-Ju Kim, et al.
Biomarker Research (2025) Vol. 13, Iss. 1
Open Access
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