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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:

Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features
Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, et al.
mAbs (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 25

Showing 25 citing articles:

Biophysics-based protein language models for protein engineering
Sam Gelman, Bryce Johnson, Chase R. Freschlin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 9
Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions
Doo Nam Kim, Andrew McNaughton, Neeraj Kumar
Bioengineering (2024) Vol. 11, Iss. 2, pp. 185-185
Open Access | Times Cited: 7
Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability
Habib Bashour, Eva Smorodina, Matteo Pariset, et al.
Communications Biology (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 6
Prediction of protein biophysical traits from limited data: a case study on nanobody thermostability through NanoMelt
Aubin Ramon, Mingyang Ni, Olga Predeina, et al.
mAbs (2025) Vol. 17, Iss. 1
Open Access
Modern machine learning methods for protein property prediction
Arjun Dosajh, P. K. Agrawal, Prathit Chatterjee, et al.
Current Opinion in Structural Biology (2025) Vol. 90, pp. 102990-102990
Closed Access
Developability assessment at early-stage discovery to enable development of antibody-derived therapeutics
Weijie Zhang, Hao Wang, Nan Feng, et al.
Antibody Therapeutics (2022) Vol. 6, Iss. 1, pp. 13-29
Open Access | Times Cited: 26
Deep learning in preclinical antibody drug discovery and development
Yuwei Zhou, Ziru Huang, Wenzhen Li, et al.
Methods (2023) Vol. 218, pp. 57-71
Closed Access | Times Cited: 16
How can we discover developable antibody-based biotherapeutics?
Joschka Bauer, Nandhini Rajagopal, Priyanka Gupta, et al.
Frontiers in Molecular Biosciences (2023) Vol. 10
Open Access | Times Cited: 14
T-cell receptor binding prediction: A machine learning revolution
Anna Weber, Aurélien Pélissier, María Rodríguez Martínez
ImmunoInformatics (2024) Vol. 15, pp. 100040-100040
Open Access | Times Cited: 4
AbMelt: Learning antibody thermostability from molecular dynamics
Zachary A. Rollins, Talal Widatalla, Alan C. Cheng, et al.
Biophysical Journal (2024) Vol. 123, Iss. 17, pp. 2921-2933
Closed Access | Times Cited: 3
Applying artificial intelligence to accelerate and de-risk antibody discovery
Astrid Musnier, Christophe Dumet, Saheli Mitra, et al.
Frontiers in Drug Discovery (2024) Vol. 4
Open Access | Times Cited: 2
Large scale paired antibody language models
Henry Kenlay, Frédéric A. Dreyer, Aleksandr Kovaltsuk, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 12, pp. e1012646-e1012646
Open Access | Times Cited: 2
High‐throughput system for the thermostability analysis of proteins
Sae Ito, Ryo Matsunaga, Makoto Nakakido, et al.
Protein Science (2024) Vol. 33, Iss. 6
Open Access | Times Cited: 1
A comprehensive overview of recent advances in generative models for antibodies
Fanxu Meng, Na Zhou, Hu Guangchun, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 2648-2660
Open Access | Times Cited: 1
Monoclonal antibodies: From magic bullet to precision weapon
Hassan Aboul-Ella, Asmaa Gohar, Aya Ahmed Ali, et al.
Molecular Biomedicine (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 1
Prediction of polyreactive and nonspecific single-chain fragment variables through structural biochemical features and protein language-based descriptors
Hocheol Lim, Kyoung Tai No
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 7
Building Representation Learning Models for Antibody Comprehension
Justin Barton, Aretas Gaspariunas, Jacob D. Galson, et al.
Cold Spring Harbor Perspectives in Biology (2023) Vol. 16, Iss. 3, pp. a041462-a041462
Closed Access | Times Cited: 2
VCAb: A web-tool for structure-guided antibody engineering
Dongjun Guo, Joseph Ng, Deborah K. Dunn‐Walters, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
IgG Structure and Function
Christy A. Thomson
Elsevier eBooks (2024)
Closed Access
Leveraging Multi-Modal Feature Learning for Predictions of Antibody Viscosity
Krishna D. B. Anapindi, Kai Liu, Willie Wang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
VCAb: A web-tool for structure-guided exploration of antibodies
Dongjun Guo, Joseph Ng, Deborah K. Dunn‐Walters, et al.
Bioinformatics Advances (2024) Vol. 4, Iss. 1
Open Access
PROPERMAB: an integrative framework for in silico prediction of antibody developability using machine learning
Li Bian, Senlin Luo, Wenhua Wang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Bridging biomolecular modalities for knowledge transfer in bio-language models
Mangal Prakash, Artem Moskalev, Peter A. DiMaggio, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Learning antibody sequence constraints from allelic inclusion
Milind Jagota, Chloe Hsu, Thomas Mazumder, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
T cell receptor binding prediction: A machine learning revolution
Anna Weber, Aurélien Pélissier, María Rodríguez Martínez
arXiv (Cornell University) (2023)
Open Access
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