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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:

Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
Morgan Thomas, Andrew Boardman, Miguel García-Ortegón, et al.
Methods in molecular biology (2021), pp. 1-59
Closed Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Intelligent Computing: The Latest Advances, Challenges, and Future
Shiqiang Zhu, Ting Yu, Tao Xu, et al.
Intelligent Computing (2023) Vol. 2
Open Access | Times Cited: 137
Integrating structure-based approaches in generative molecular design
Morgan Thomas, Andreas Bender, Chris de Graaf
Current Opinion in Structural Biology (2023) Vol. 79, pp. 102559-102559
Open Access | Times Cited: 41
Exploring the current and prospective role of artificial intelligence in disease diagnosis
Ali Aamir, Arham Iqbal, Fareeha Jawed, et al.
Annals of Medicine and Surgery (2024) Vol. 86, Iss. 2, pp. 943-949
Open Access | Times Cited: 12
QSARtuna: An Automated QSAR Modeling Platform for Molecular Property Prediction in Drug Design
Lewis Mervin, Alexey Voronov, Mikhail A. Kabeshov, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 14, pp. 5365-5374
Open Access | Times Cited: 8
Explainable artificial intelligence: A taxonomy and guidelines for its application to drug discovery
Ignacio Ponzoni, Juan Antonio Páez Prosper, Nuria E. Campillo
Wiley Interdisciplinary Reviews Computational Molecular Science (2023) Vol. 13, Iss. 6
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
MolScore: a scoring, evaluation and benchmarking framework for generative models in de novo drug design
Morgan Thomas, N.M. O'Boyle, Andreas Bender, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 5
Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation
Morgan Thomas, N.M. O'Boyle, Andreas Bender, et al.
Journal of Cheminformatics (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 21
Qptuna: an automated QSAR modelling platform for molecular property prediction in drug design
Lewis Mervin, Alexey Voronov, Mikhail A. Kabeshov, et al.
(2024)
Open Access | Times Cited: 3
ACEGEN: Reinforcement Learning of Generative Chemical Agents for Drug Discovery
Albert Bou, Morgan Thomas, Sebastian Dittert, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 15, pp. 5900-5911
Open Access | Times Cited: 3
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data
Koichi Handa, Morgan Thomas, Michiharu Kageyama, et al.
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 8
Artificial Intelligence Techniques in the Classification and Screening of Compounds in Computer‐Aided Drug Design (CADD) Process
Raghunath Satpathy
(2024), pp. 473-497
Closed Access | Times Cited: 2
Fundamentals of Molecular Docking and Comparative Analysis of Protein–Small-Molecule Docking Approaches
Sefika Feyza Maden, Selin Sezer, Saliha Ece Acuner
Biomedical engineering (2022)
Open Access | Times Cited: 8
MolScore: A scoring and evaluation framework for de novo drug design
Morgan Thomas, N.M. O'Boyle, Andreas Bender, et al.
(2024)
Open Access | Times Cited: 1
QSARtuna: an automated QSAR modelling platform for molecular property prediction in drug design
Lewis Mervin, Alexey Voronov, Mikhail A. Kabeshov, et al.
(2024)
Open Access | Times Cited: 1
Chemo-enzymatic synthesis of bioactive compounds from traditional Chinese medicine and medicinal plants
Shuang Liu, Shuo Yang, Ping Su
Science of Traditional Chinese Medicine (2024) Vol. 2, Iss. 2, pp. 95-103
Open Access | Times Cited: 1
Calibrated prediction of scarce adverse drug reaction labels with conditional neural processes
Miguel García-Ortegón, Srijit Seal, Shantanu Singh, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Design Green Chemicals by Predicting Vaporization Properties Using Explainable Graph Attention Networks
Yeonjoon Kim, Jaeyoung Cho, Hojin Jung, et al.
(2024)
Open Access | Times Cited: 1
Recurrent neural network (RNN) model accelerates the development of antibacterial metronidazole derivatives
Nannan Chen, Lijuan Yang, Na Ding, et al.
RSC Advances (2022) Vol. 12, Iss. 35, pp. 22893-22901
Open Access | Times Cited: 6
Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation
Morgan Thomas, N.M. O'Boyle, Andreas Bender, et al.
(2022)
Open Access | Times Cited: 6
MolScore: A scoring and evaluation framework for de novo drug design
Morgan Thomas, N.M. O'Boyle, Andreas Bender, et al.
(2023)
Open Access | Times Cited: 3
DataPype: A Fully Automated Unified Software Platform for Computer-Aided Drug Design
Mohemmed Faraz Khan, Shubhangi Kandwal, Darren Fayne
ACS Omega (2023) Vol. 8, Iss. 42, pp. 39468-39480
Open Access | Times Cited: 3
Molecular Docking - Recent Advances
Erman Salih İstifli, Erman Salih, Sefika Feyza Maden, et al.
Biomedical engineering (2022)
Open Access | Times Cited: 5
On The Difficulty of Validating Molecular Generative Models Realistically: A Case Study on Public and Proprietary Data
Koichi Handa, Morgan Thomas, Michiharu Kageyama, et al.
(2023)
Open Access | Times Cited: 2
De novo generated combinatorial library design
Simon Johansson, Morteza Haghir Chehreghani, Ola Engkvist, et al.
Digital Discovery (2023) Vol. 3, Iss. 1, pp. 122-135
Open Access | Times Cited: 2
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