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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:

Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases
Christophe Müller, Obdulia Rabal, Constantino Diaz Gonzalez
Methods in molecular biology (2021), pp. 383-407
Closed Access | Times Cited: 20

Showing 20 citing articles:

AlphaFold2 protein structure prediction: Implications for drug discovery
Neera Borkakoti, Janet M. Thornton
Current Opinion in Structural Biology (2023) Vol. 78, pp. 102526-102526
Open Access | Times Cited: 54
Deep learning in prediction of intrinsic disorder in proteins
Bi Zhao, Lukasz Kurgan
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 1286-1294
Open Access | Times Cited: 40
Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditions
Lung-Yi Chen, Yi‐Pei Li
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 7
Transitioning towards Net-Zero Emissions in Chemical and Process Industries: A Holistic Perspective
Peter Glavič, Zorka Novak Pintarič, Helena Levičnik, et al.
Processes (2023) Vol. 11, Iss. 9, pp. 2647-2647
Open Access | Times Cited: 13
Artificial Intelligence in Drug Design
Alexander Heifetz
Methods in molecular biology (2021)
Closed Access | Times Cited: 27
Combining structure-based pharmacophore modeling and machine learning for the identification of novel BTK inhibitors
Tanuj Sharma, Venu Venkatarame Gowda Saralamma, Duk‐Chul Lee, et al.
International Journal of Biological Macromolecules (2022) Vol. 222, pp. 239-250
Closed Access | Times Cited: 12
Computational Approaches and Drug Discovery: Where Are We Going?
Marco Tutone, Anna Maria Almerico
Molecules (2024) Vol. 29, Iss. 5, pp. 969-969
Open Access | Times Cited: 1
Accelerating COVID-19 Drug Discovery with High-Performance Computing
Alexander Heifetz
Methods in molecular biology (2023), pp. 405-411
Closed Access | Times Cited: 3
A toolkit for covalent docking with GOLD: from automated ligand preparation with KNIME to bound protein–ligand complexes
Laurianne David, Anissa Mdahoma, Natesh Singh, et al.
Bioinformatics Advances (2022) Vol. 2, Iss. 1
Open Access | Times Cited: 5
Transitioning Towards Net Zero Emissions in the Chemical and Process Industries: A Holistic Perspective
Peter Glavič, Zorka Novak Pintarič, Helena Levičnik, et al.
(2023)
Open Access | Times Cited: 2
Molecular Dynamics and Other HPC Simulations for Drug Discovery
Martin Kotev, Constantino Diaz Gonzalez
Methods in molecular biology (2023), pp. 265-291
Closed Access | Times Cited: 2
Protoporphyrinogen oxidase inhibitors discovered by Artificial Intelligence platform
Abigail L. Barker, Yosef Geva, Eyal Simonovsky, et al.
Advances in Weed Science (2023) Vol. 41
Open Access | Times Cited: 2
Leveraging DFT and Molecular Fragmentation for Chemically Accurate pKa Prediction Using Machine Learning
Alec J. Sanchez, Sarah Maier, Krishnan Raghavachari
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 3, pp. 712-723
Closed Access
Quantum‐Enabled Drug Discovery Process
Abhishek Rao, Deepika Kumari, Satyendra Singh, et al.
(2024), pp. 27-55
Closed Access
Machine learning models to identify lead compound and substitution optimization to have derived energetics and conformational stability through docking and MD simulations for sphingosine kinase 1
Anantha Krishnan Dhanabalan, D. Velmurugan, Jebiti Haribabu, et al.
Molecular Diversity (2024)
Closed Access
Exploring the future of biopharmaceutical drug discovery: can advanced AI platforms overcome current challenges?
Alberto Bettanti, Andrea R. Beccari, Marco Biccarino
Discover Artificial Intelligence (2024) Vol. 4, Iss. 1
Open Access
AttenhERG: a reliable and interpretable graph neural network framework for predicting hERG channel blockers
Tianbiao Yang, Xiaoyu Ding, Elizabeth McMichael, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access
On the importance for drug discovery of a transnational Latin American database of natural compound structures
Timothy M. Thomson
Frontiers in Pharmacology (2023) Vol. 14
Open Access | Times Cited: 1
Asenapine as a Potential Lead Inhibitor against Central Ca2+/Calmodulin-Dependent Protein Kinase II: Investigation by Docking Simulation and Experimental Validation
Safa Daoud, Reem Fawaz Abutayeh, Shada J. Alabed, et al.
The Open Medicinal Chemistry Journal (2023) Vol. 17, Iss. 1
Open Access
Identification of Pharmacophoric Fragments of DYRK1A Inhibitors Using Machine Learning Classification Models
Mengzhou Bi, Zhen Guan, Tengjiao Fan, et al.
Molecules (2022) Vol. 27, Iss. 6, pp. 1753-1753
Open Access
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