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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:

Beam Search for Automated Design and Scoring of Novel ROR Ligands with Machine Intelligence**
Michaël Moret, Moritz Helmstädter, Francesca Grisoni, et al.
Angewandte Chemie International Edition (2021) Vol. 60, Iss. 35, pp. 19477-19482
Open Access | Times Cited: 72

Showing 1-25 of 72 citing articles:

Artificial intelligence for natural product drug discovery
Michael W. Mullowney, Katherine Duncan, Somayah S. Elsayed, et al.
Nature Reviews Drug Discovery (2023) Vol. 22, Iss. 11, pp. 895-916
Closed Access | Times Cited: 111
Evaluation guidelines for machine learning tools in the chemical sciences
Andreas Bender, Nadine Schneider, Marwin Segler, et al.
Nature Reviews Chemistry (2022) Vol. 6, Iss. 6, pp. 428-442
Closed Access | Times Cited: 95
Leveraging molecular structure and bioactivity with chemical language models for de novo drug design
Michaël Moret, Irène Pachón-Angona, Leandro Cotos, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open 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: 81
Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR
Alexander Tropsha, Olexandr Isayev, Alexandre Varnek, et al.
Nature Reviews Drug Discovery (2023) Vol. 23, Iss. 2, pp. 141-155
Closed Access | Times Cited: 77
Chemical language models for de novo drug design: Challenges and opportunities
Francesca Grisoni
Current Opinion in Structural Biology (2023) Vol. 79, pp. 102527-102527
Open Access | Times Cited: 53
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: 18
Machine learning-aided generative molecular design
Yuanqi Du, Arian R. Jamasb, Jeff Guo, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 6, pp. 589-604
Closed Access | Times Cited: 18
Generative artificial intelligence in drug discovery: basic framework, recent advances, challenges, and opportunities
Amit Gangwal, M. Azim Ansari, Iqrar Ahmad, et al.
Frontiers in Pharmacology (2024) Vol. 15
Open Access | Times Cited: 17
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: 12
Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries
Shree Sowndarya S. V., Jeffrey Law, Charles Tripp, et al.
Nature Machine Intelligence (2022) Vol. 4, Iss. 8, pp. 720-730
Open Access | Times Cited: 51
Advances and Challenges in De Novo Drug Design Using Three-Dimensional Deep Generative Models
Weixin Xie, Fanhao Wang, Yibo Li, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 10, pp. 2269-2279
Closed Access | Times Cited: 47
Structure‐Based Drug Discovery with Deep Learning**
Rıza Özçelik, Derek van Tilborg, José Jiménez-Luna, et al.
ChemBioChem (2023) Vol. 24, Iss. 13
Open Access | Times Cited: 33
Deep Learning-Based Bioactive Therapeutic Peptide Generation and Screening
Haiping Zhang, Konda Mani Saravanan, Yanjie Wei, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 3, pp. 835-845
Open Access | Times Cited: 32
De Novo Design of Nurr1 Agonists via Fragment-Augmented Generative Deep Learning in Low-Data Regime
Marco Ballarotto, Sabine Willems, Tanja Stiller, et al.
Journal of Medicinal Chemistry (2023) Vol. 66, Iss. 12, pp. 8170-8177
Open Access | Times Cited: 24
Variational autoencoder-based chemical latent space for large molecular structures with 3D complexity
Toshiki Ochiai, Tensei Inukai, Manato Akiyama, et al.
Communications Chemistry (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 19
Chemogenomics for NR1 nuclear hormone receptors
Laura Isigkeit, Espen Schallmayer, Romy Busch, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 6
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: 6
Chemogenomics for steroid hormone receptors (NR3)
Espen Schallmayer, Laura Isigkeit, Lewis Elson, et al.
Communications Chemistry (2025) Vol. 8, Iss. 1
Open Access
DeLA-Drug: A Deep Learning Algorithm for Automated Design of Druglike Analogues
Teresa Maria Creanza, Giuseppe Lamanna, Pietro Delre, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 6, pp. 1411-1424
Closed Access | Times Cited: 26
Development of a Potent Nurr1 Agonist Tool for In Vivo Applications
Jan Vietor, Christian Gege, Tanja Stiller, et al.
Journal of Medicinal Chemistry (2023) Vol. 66, Iss. 9, pp. 6391-6402
Open Access | Times Cited: 18
GENERA: A Combined Genetic/Deep-Learning Algorithm for Multiobjective Target-Oriented De Novo Design
G. Lamanna, Pietro Delre, Gilles Marcou, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 16, pp. 5107-5119
Open Access | Times Cited: 15
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: 4
Cyclobutane-containing scaffolds in bioactive small molecules
Chunngai Hui, Yang Liu, Mao Jiang, et al.
Trends in Chemistry (2022) Vol. 4, Iss. 8, pp. 677-681
Closed Access | Times Cited: 25
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