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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:

Protein complex prediction with AlphaFold-Multimer
Richard Evans, M. E. O’Neill, Alexander Pritzel, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 2942

Showing 26-50 of 2942 citing articles:

How good are AlphaFold models for docking-based virtual screening?
Valeria Scardino, Juan I. Di Filippo, Claudio N. Cavasotto
iScience (2022) Vol. 26, Iss. 1, pp. 105920-105920
Open Access | Times Cited: 119
What's next for AlphaFold and the AI protein-folding revolution
Ewen Callaway
Nature (2022) Vol. 604, Iss. 7905, pp. 234-238
Open Access | Times Cited: 118
Can we predict T cell specificity with digital biology and machine learning?
D. R. Hudson, Ricardo A. Fernandes, Mark Basham, et al.
Nature reviews. Immunology (2023) Vol. 23, Iss. 8, pp. 511-521
Open Access | Times Cited: 118
De novo design of protein interactions with learned surface fingerprints
Pablo Gaínza, Sarah Wehrle, Alexandra Van Hall‐Beauvais, et al.
Nature (2023) Vol. 617, Iss. 7959, pp. 176-184
Open Access | Times Cited: 118
BepiPred‐3.0: Improved B‐cell epitope prediction using protein language models
Joakim Nøddeskov Clifford, Magnus Haraldson Høie, Sebastian Deleuran, et al.
Protein Science (2022) Vol. 31, Iss. 12
Open Access | Times Cited: 117
Large AI Models in Health Informatics: Applications, Challenges, and the Future
Jianing Qiu, Lin Li, Jiankai Sun, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 12, pp. 6074-6087
Open Access | Times Cited: 115
Ins and outs of AlphaFold2 transmembrane protein structure predictions
Tamás Hegedűs, Markus Geisler, Gergely L. Lukács, et al.
Cellular and Molecular Life Sciences (2022) Vol. 79, Iss. 1
Open Access | Times Cited: 110
Visualization of translation and protein biogenesis at the ER membrane
Max Gemmer, Marten L. Chaillet, Joyce van Loenhout, et al.
Nature (2023) Vol. 614, Iss. 7946, pp. 160-167
Open Access | Times Cited: 109
The structural coverage of the human proteome before and after AlphaFold
Eduard Porta‐Pardo, Victoria Ruiz‐Serra, Samuel Valentini, et al.
PLoS Computational Biology (2022) Vol. 18, Iss. 1, pp. e1009818-e1009818
Open Access | Times Cited: 107
Cryo-EM advances in RNA structure determination
Haiyun Ma, Xinyu Jia, Kaiming Zhang, et al.
Signal Transduction and Targeted Therapy (2022) Vol. 7, Iss. 1
Open Access | Times Cited: 106
Mechanisms and pathology of protein misfolding and aggregation
Nikolaos Louros, Joost Schymkowitz, Frédéric Rousseau
Nature Reviews Molecular Cell Biology (2023) Vol. 24, Iss. 12, pp. 912-933
Closed Access | Times Cited: 105
Deep learning and protein structure modeling
Minkyung Baek, David Baker
Nature Methods (2022) Vol. 19, Iss. 1, pp. 13-14
Closed Access | Times Cited: 103
Identification and functional characterization of transcriptional activators in human cells
Nader Alerasool, He Leng, Zhen‐Yuan Lin, et al.
Molecular Cell (2022) Vol. 82, Iss. 3, pp. 677-695.e7
Open Access | Times Cited: 103
Improving peptide-protein docking with AlphaFold-Multimer using forced sampling
Isak Johansson-Åkhe, Björn Wallner
Frontiers in Bioinformatics (2022) Vol. 2
Open Access | Times Cited: 102
Protein complexes in cells by AI‐assisted structural proteomics
Francis J. O’Reilly, Andrea Graziadei, Christian Forbrig, et al.
Molecular Systems Biology (2023) Vol. 19, Iss. 4
Open Access | Times Cited: 94
Structure-based prediction of T cell receptor:peptide-MHC interactions
Philip Bradley
eLife (2023) Vol. 12
Open Access | Times Cited: 93
ATG9A and ATG2A form a heteromeric complex essential for autophagosome formation
Alexander R. van Vliet, George N. Chiduza, Sarah Maslen, et al.
Molecular Cell (2022) Vol. 82, Iss. 22, pp. 4324-4339.e8
Open Access | Times Cited: 91
Computational and artificial intelligence-based methods for antibody development
Ji‐Sun Kim, Matthew McFee, Qiao Fang, et al.
Trends in Pharmacological Sciences (2023) Vol. 44, Iss. 3, pp. 175-189
Open Access | Times Cited: 89
Axonemal structures reveal mechanoregulatory and disease mechanisms
Travis Walton, Miao Gui, Simona A. Velkova, et al.
Nature (2023) Vol. 618, Iss. 7965, pp. 625-633
Open Access | Times Cited: 86
The structural context of posttranslational modifications at a proteome-wide scale
Isabell Bludau, Sander Willems, Wenfeng Zeng, et al.
PLoS Biology (2022) Vol. 20, Iss. 5, pp. e3001636-e3001636
Open Access | Times Cited: 84
Uncovering new families and folds in the natural protein universe
Janani Durairaj, Andrew Waterhouse, Toomas Mets, et al.
Nature (2023) Vol. 622, Iss. 7983, pp. 646-653
Open Access | Times Cited: 81
The impact of AlphaFold Protein Structure Database on the fields of life sciences
Mihály Váradi, Sameer Velankar
PROTEOMICS (2022) Vol. 23, Iss. 17
Open Access | Times Cited: 80
Exploring the potential of time-series transformers for process modeling and control in chemical systems: An inevitable paradigm shift?
Niranjan Sitapure, Joseph Sang‐Il Kwon
Process Safety and Environmental Protection (2023) Vol. 194, pp. 461-477
Closed Access | Times Cited: 80
AI-Based Protein Structure Prediction in Drug Discovery: Impacts and Challenges
Michael Schauperl, R. Aldrin Denny
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 13, pp. 3142-3156
Closed Access | Times Cited: 79
Comparative studies of AlphaFold, RoseTTAFold and Modeller: a case study involving the use of G-protein-coupled receptors
Chien Lee, Bo‐Han Su, Yufeng Jane Tseng
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Open Access | Times Cited: 79

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