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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:

Predicting the mutational drivers of future SARS-CoV-2 variants of concern
M. Cyrus Maher, István Bartha, Steven Weaver, et al.
Science Translational Medicine (2022) Vol. 14, Iss. 633
Open Access | Times Cited: 156

Showing 1-25 of 156 citing articles:

The evolution of SARS-CoV-2
Peter V. Markov, Mahan Ghafari, Martin Beer, et al.
Nature Reviews Microbiology (2023) Vol. 21, Iss. 6, pp. 361-379
Open Access | Times Cited: 676
Efficient evolution of human antibodies from general protein language models
Brian Hie, Varun R. Shanker, Duo Xu, et al.
Nature Biotechnology (2023) Vol. 42, Iss. 2, pp. 275-283
Open Access | Times Cited: 203
Deep mutational scans for ACE2 binding, RBD expression, and antibody escape in the SARS-CoV-2 Omicron BA.1 and BA.2 receptor-binding domains
Tyler N. Starr, Allison J. Greaney, Cameron Stewart, et al.
PLoS Pathogens (2022) Vol. 18, Iss. 11, pp. e1010951-e1010951
Open Access | Times Cited: 160
The Evolution and Biology of SARS-CoV-2 Variants
Amalio Telenti, Emma B. Hodcroft, David L. Robertson
Cold Spring Harbor Perspectives in Medicine (2022) Vol. 12, Iss. 5, pp. a041390-a041390
Open Access | Times Cited: 152
A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike
Bernadeta Dadonaite, Katharine H. D. Crawford, Caelan E. Radford, et al.
Cell (2023) Vol. 186, Iss. 6, pp. 1263-1278.e20
Open Access | Times Cited: 127
Evolutionary velocity with protein language models predicts evolutionary dynamics of diverse proteins
Brian Hie, Kevin Yang, Peter S. Kim
Cell Systems (2022) Vol. 13, Iss. 4, pp. 274-285.e6
Open Access | Times Cited: 85
COVID-19: Challenges of Viral Variants
Jana L. Jacobs, Ghady Haidar, John W. Mellors
Annual Review of Medicine (2022) Vol. 74, Iss. 1, pp. 31-53
Open Access | Times Cited: 82
An early warning system for emerging SARS-CoV-2 variants
Lorenzo Subissi, Anne von Gottberg, Lipi Thukral, et al.
Nature Medicine (2022) Vol. 28, Iss. 6, pp. 1110-1115
Open Access | Times Cited: 69
Fitness effects of mutations to SARS-CoV-2 proteins
Jesse D. Bloom, Richard A. Neher
Virus Evolution (2023) Vol. 9, Iss. 2
Open Access | Times Cited: 67
From Alpha to Omicron: How Different Variants of Concern of the SARS-Coronavirus-2 Impacted the World
Mickensone Andre, Lee-Seng Lau, Marissa D. Pokharel, et al.
Biology (2023) Vol. 12, Iss. 9, pp. 1267-1267
Open Access | Times Cited: 41
Deep-learning-enabled protein–protein interaction analysis for prediction of SARS-CoV-2 infectivity and variant evolution
Guangyu Wang, Xiaohong Liu, Kai Wang, et al.
Nature Medicine (2023) Vol. 29, Iss. 8, pp. 2007-2018
Closed Access | Times Cited: 40
Using big sequencing data to identify chronic SARS-Coronavirus-2 infections
Sheri Harari, Danielle Miller, Shay Fleishon, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 12
Towards evolutionary predictions: Current promises and challenges
Meike T. Wortel, Deepa Agashe, Susan F. Bailey, et al.
Evolutionary Applications (2022) Vol. 16, Iss. 1, pp. 3-21
Open Access | Times Cited: 47
Spread of Gamma (P.1) Sub-Lineages Carrying Spike Mutations Close to the Furin Cleavage Site and Deletions in the N-Terminal Domain Drives Ongoing Transmission of SARS-CoV-2 in Amazonas, Brazil
Felipe Gomes Naveca, Valdinete Alves do Nascimento, Victor Costa de Souza, et al.
Microbiology Spectrum (2022) Vol. 10, Iss. 1
Open Access | Times Cited: 40
SARS-CoV-2 evolved variants optimize binding to cellular glycocalyx
Sang Hoon Kim, Fiona L. Kearns, Mia A. Rosenfeld, et al.
Cell Reports Physical Science (2023) Vol. 4, Iss. 4, pp. 101346-101346
Open Access | Times Cited: 34
Predicting the antigenic evolution of SARS-COV-2 with deep learning
Wenkai Han, Ningning Chen, Xinzhou Xu, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 31
Fitness effects of mutations to SARS-CoV-2 proteins
Jesse D. Bloom, Richard A. Neher
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 30
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics
Maxim Zvyagin, Alexander Brace, Kyle Hippe, et al.
The International Journal of High Performance Computing Applications (2023) Vol. 37, Iss. 6, pp. 683-705
Open Access | Times Cited: 27
A mathematical model for COVID-19 considering waning immunity, vaccination and control measures
Subhas Kumar Ghosh, Sachchit Ghosh
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 25
An intranasal influenza virus-vectored vaccine prevents SARS-CoV-2 replication in respiratory tissues of mice and hamsters
Shaofeng Deng, Ying Liu, Rachel Chun-Yee Tam, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 25
Deep mutational scanning of SARS-CoV-2 Omicron BA.2.86 and epistatic emergence of the KP.3 variant
Ashley L. Taylor, Tyler N. Starr
Virus Evolution (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 7
Genotype-Structured Modeling of Variant Emergence and Its Impact on Virus Infection
Anass Bouchnita
Mathematics (2025) Vol. 13, Iss. 1, pp. 167-167
Open Access
Inferring effects of mutations on SARS-CoV-2 transmission from genomic surveillance data
Brian Lee, Ahmed Abdul Quadeer, Muhammad S. Sohail, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges
Yang Ye, Abhishek Pandey, Carolyn E. Bawden, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
Paying attention to the SARS-CoV-2 dialect : a deep neural network approach to predicting novel protein mutations
Magdalyn E. Elkin, Xingquan Zhu
Communications Biology (2025) Vol. 8, Iss. 1
Open Access
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