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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:

Molecular representations in AI-driven drug discovery: a review and practical guide
Laurianne David, Amol Thakkar, Rocío Mercado, et al.
Journal of Cheminformatics (2020) Vol. 12, Iss. 1
Open Access | Times Cited: 384

Showing 1-25 of 384 citing articles:

Why 90% of clinical drug development fails and how to improve it?
Duxin Sun, Wei Gao, Hongxiang Hu, et al.
Acta Pharmaceutica Sinica B (2022) Vol. 12, Iss. 7, pp. 3049-3062
Open Access | Times Cited: 764
Molecular contrastive learning of representations via graph neural networks
Yuyang Wang, Jianren Wang, Zhonglin Cao, et al.
Nature Machine Intelligence (2022) Vol. 4, Iss. 3, pp. 279-287
Closed Access | Times Cited: 405
AI for life: Trends in artificial intelligence for biotechnology
Andreas Holzinger, Katharina Keiblinger, Petr Holub, et al.
New Biotechnology (2023) Vol. 74, pp. 16-24
Open Access | Times Cited: 240
Advances in De Novo Drug Design: From Conventional to Machine Learning Methods
Varnavas D. Mouchlis, Antreas Afantitis, Angela Serra, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 4, pp. 1676-1676
Open Access | Times Cited: 229
A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis
Tobias Gensch, Gabriel dos Passos Gomes, Pascal Friederich, et al.
Journal of the American Chemical Society (2022) Vol. 144, Iss. 3, pp. 1205-1217
Closed Access | Times Cited: 213
Machine Learning in Chemical Engineering: Strengths, Weaknesses, Opportunities, and Threats
Maarten R. Dobbelaere, Pieter Plehiers, Ruben Van de Vijver, et al.
Engineering (2021) Vol. 7, Iss. 9, pp. 1201-1211
Open Access | Times Cited: 191
Graph representation learning in biomedicine and healthcare
Michelle M. Li, Kexin Huang, Marinka Żitnik
Nature Biomedical Engineering (2022) Vol. 6, Iss. 12, pp. 1353-1369
Open Access | Times Cited: 144
Generative Models as an Emerging Paradigm in the Chemical Sciences
Dylan M. Anstine, Olexandr Isayev
Journal of the American Chemical Society (2023) Vol. 145, Iss. 16, pp. 8736-8750
Open Access | Times Cited: 142
Automation and computer-assisted planning for chemical synthesis
Yuning Shen, Julia E. Borowski, Melissa A. Hardy, et al.
Nature Reviews Methods Primers (2021) Vol. 1, Iss. 1
Closed Access | Times Cited: 128
AI in drug discovery and its clinical relevance
Rizwan Qureshi, Muhammad Irfan, Taimoor Muzaffar Gondal, et al.
Heliyon (2023) Vol. 9, Iss. 7, pp. e17575-e17575
Open Access | Times Cited: 124
Deep generative molecular design reshapes drug discovery
Xiangxiang Zeng, Fei Wang, Yuan Luo, et al.
Cell Reports Medicine (2022) Vol. 3, Iss. 12, pp. 100794-100794
Open Access | Times Cited: 120
Artificial intelligence for drug discovery: Resources, methods, and applications
Wei Chen, Xuesong Liu, Sanyin Zhang, et al.
Molecular Therapy — Nucleic Acids (2023) Vol. 31, pp. 691-702
Open Access | Times Cited: 110
Molecular design in drug discovery: a comprehensive review of deep generative models
Yu Cheng, Yongshun Gong, Yuansheng Liu, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 103
Artificial intelligence in drug discovery: applications and techniques
Jianyuan Deng, Zhibo Yang, Iwao Ojima, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 98
Small molecules and their impact in drug discovery: A perspective on the occasion of the 125th anniversary of the Bayer Chemical Research Laboratory
Hartmut Beck, Michael Härter, B. Hass, et al.
Drug Discovery Today (2022) Vol. 27, Iss. 6, pp. 1560-1574
Open Access | Times Cited: 97
Extending machine learning beyond interatomic potentials for predicting molecular properties
Nikita Fedik, R.I. Zubatyuk, Maksim Kulichenko, et al.
Nature Reviews Chemistry (2022) Vol. 6, Iss. 9, pp. 653-672
Closed Access | Times Cited: 85
Generative machine learning for de novo drug discovery: A systematic review
Dominic D. Martinelli
Computers in Biology and Medicine (2022) Vol. 145, pp. 105403-105403
Closed Access | Times Cited: 82
Artificial intelligence to bring nanomedicine to life
Nikita Serov, Vladimir V. Vinogradov
Advanced Drug Delivery Reviews (2022) Vol. 184, pp. 114194-114194
Closed Access | Times Cited: 76
New Opportunity: Machine Learning for Polymer Materials Design and Discovery
Pengcheng Xu, Huimin Chen, Minjie Li, et al.
Advanced Theory and Simulations (2022) Vol. 5, Iss. 5
Closed Access | Times Cited: 70
Scoring Functions for Protein-Ligand Binding Affinity Prediction Using Structure-based Deep Learning: A Review
Rocco Meli, Garrett M. Morris, Philip C. Biggin
Frontiers in Bioinformatics (2022) Vol. 2
Open Access | Times Cited: 70
Deep learning methods for drug response prediction in cancer: Predominant and emerging trends
Alexander Partin, Thomas Brettin, Yitan Zhu, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 61
A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions
Bharti Khemani, Shruti Patil, Ketan Kotecha, et al.
Journal Of Big Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 61
Revolutionizing Medicinal Chemistry: The Application of Artificial Intelligence (AI) in Early Drug Discovery
Ri Han, Hongryul Yoon, Gahee Kim, et al.
Pharmaceuticals (2023) Vol. 16, Iss. 9, pp. 1259-1259
Open Access | Times Cited: 60
A systematic study of key elements underlying molecular property prediction
Jianyuan Deng, Zhibo Yang, Hehe Wang, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 56
Discovery of senolytics using machine learning
Vanessa Smer-Barreto, Andrea Quintanilla, Richard Elliott, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 44
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