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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:

Antibody structure prediction using interpretable deep learning
Jeffrey A. Ruffolo, Jeremias Sulam, Jeffrey J. Gray
Patterns (2021) Vol. 3, Iss. 2, pp. 100406-100406
Open Access | Times Cited: 158

Showing 1-25 of 158 citing articles:

Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
Jeffrey A. Ruffolo, Lee‐Shin Chu, Sai Pooja Mahajan, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 166
ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins
Brennan Abanades, Wing Ki Wong, Fergus Boyles, et al.
Communications Biology (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 160
Designing antibodies as therapeutics
Paul J. Carter, Arvind Rajpal
Cell (2022) Vol. 185, Iss. 15, pp. 2789-2805
Open Access | Times Cited: 137
Deciphering the language of antibodies using self-supervised learning
Jinwoo Leem, L. Mitchell, James H. R. Farmery, et al.
Patterns (2022) Vol. 3, Iss. 7, pp. 100513-100513
Open Access | Times Cited: 99
Ig-VAE: Generative modeling of protein structure by direct 3D coordinate generation
Raphael R. Eguchi, Christian A. Choe, Po‐Ssu Huang
PLoS Computational Biology (2022) Vol. 18, Iss. 6, pp. e1010271-e1010271
Open Access | Times Cited: 90
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
Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies
Rahmad Akbar, Habib Bashour, Puneet Rawat, et al.
mAbs (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 82
In silico proof of principle of machine learning-based antibody design at unconstrained scale
Rahmad Akbar, Philippe A. Robert, Cédric R. Weber, et al.
mAbs (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 75
Development of therapeutic antibodies for the treatment of diseases
Zeng Wang, Guoqing Wang, Huaqing Lu, et al.
Molecular Biomedicine (2022) Vol. 3, Iss. 1
Open Access | Times Cited: 75
Drug discovery and development: introduction to the general public and patient groups
Natesh Singh, Philippe Vayer, Shivalika Tanwar, et al.
Frontiers in Drug Discovery (2023) Vol. 3
Open Access | Times Cited: 70
Advances in computational structure-based antibody design
Alissa Hummer, Brennan Abanades, Charlotte M. Deane
Current Opinion in Structural Biology (2022) Vol. 74, pp. 102379-102379
Open Access | Times Cited: 69
Artificial Intelligence in Pharmaceutical Sciences
Mingkun Lu, Jiayi Yin, Qi Zhu, et al.
Engineering (2023) Vol. 27, pp. 37-69
Open Access | Times Cited: 64
Assessing developability early in the discovery process for novel biologics
Monica L. Fernández‐Quintero, Anne Ljungars, Franz Waibl, et al.
mAbs (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 50
Nanobodies: Robust miniprotein binders in biomedicine
Jeffrey Yong Joon Kim, Zhe Sang, Yufei Xiang, et al.
Advanced Drug Delivery Reviews (2023) Vol. 195, pp. 114726-114726
Open Access | Times Cited: 42
Development and use of machine learning algorithms in vaccine target selection
Barbara Bravi
npj Vaccines (2024) Vol. 9, Iss. 1
Open Access | Times Cited: 31
NanoNet: Rapid and accurate end-to-end nanobody modeling by deep learning
Tomer Cohen, Matan Halfon, Dina Schneidman‐Duhovny
Frontiers in Immunology (2022) Vol. 13
Open Access | Times Cited: 67
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures
Shitong Luo, Yufeng Su, Xingang Peng, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 64
Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery
Wiktoria Wilman, Sonia Wróbel, Weronika Bielska, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 4
Open Access | Times Cited: 59
Antibody optimization enabled by artificial intelligence predictions of binding affinity and naturalness
Sharrol Bachas, Goran Rakočević, David A. Spencer, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Closed Access | Times Cited: 42
Antibody variable region engineering for improving cancer immunotherapy
Hantao Lou, Xuetao Cao
Cancer Communications (2022) Vol. 42, Iss. 9, pp. 804-827
Open Access | Times Cited: 38
Linguistically inspired roadmap for building biologically reliable protein language models
Mai Ha Vu, Rahmad Akbar, Philippe A. Robert, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 5, pp. 485-496
Closed Access | Times Cited: 34
Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens
Federica Guarra, Giorgio Colombo
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 16, pp. 5315-5333
Open Access | Times Cited: 32
Challenges in antibody structure prediction
Monica L. Fernández‐Quintero, Janik Kokot, Franz Waibl, et al.
mAbs (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 30
The RESP AI model accelerates the identification of tight-binding antibodies
Jonathan Parkinson, Ryan Hard, Wei Wang
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 29
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: 28
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