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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:

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: 16

Showing 16 citing articles:

Learning from Protein Engineering by Deconvolution of Multi‐Mutational Variants
Frank Hollmann, Joaquin Sanchis, Manfred T. Reetz
Angewandte Chemie International Edition (2024) Vol. 63, Iss. 36
Open Access | Times Cited: 16
Best practices for machine learning in antibody discovery and development
Leonard Wossnig, Norbert Furtmann, Andrew Buchanan, et al.
Drug Discovery Today (2024) Vol. 29, Iss. 7, pp. 104025-104025
Open Access | Times Cited: 8
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: 6
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
Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools
Varun Dewaker, Vivek Kumar Morya, Yeon-Ju Kim, et al.
Biomarker Research (2025) Vol. 13, Iss. 1
Open Access
Trends and Challenges in Bispecific Antibody Production
Mikhail S. Karbyshev, Irina Kalashnikova, Veronika Dubrovskaya, et al.
Journal of Chromatography A (2025), pp. 465722-465722
Closed Access
PROPERMAB: an integrative framework for in silico prediction of antibody developability using machine learning
Li Bian, Senlin Luo, Wenhua Wang, et al.
mAbs (2025) Vol. 17, Iss. 1
Open Access
Impact of Excipient Extraction and Buffer Exchange on Recombinant Monoclonal Antibody Stability
Deepika Sarin, Kunal Krishna, M. Reza Nejadnik, et al.
Molecular Pharmaceutics (2024) Vol. 21, Iss. 4, pp. 1872-1883
Open Access | Times Cited: 3
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: 3
Assessment and incorporation of in vitro correlates to pharmacokinetic outcomes in antibody developability workflows
Tushar Jain, Bianka Prinz, Alexander Marker, et al.
mAbs (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 3
Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability
Habib Bashour, Eva Smorodina, Matteo Pariset, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
Lernen aus Protein‐Engineering durch Dekonvolution von Multi‐Mutationalen Enzymvarianten**
Frank Hollmann, Joaquin Sanchis, Manfred T. Reetz
Angewandte Chemie (2024) Vol. 136, Iss. 36
Open Access
Conserved heavy/light contacts and germline preferences revealed by a large-scale analysis of natively paired human antibody sequences and structural data.
Paweł Dudzic, Dawid Chomicz, Weronika Bielska, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Liquid-phase separations coupled with ion mobility-mass spectrometry for next-generation biopharmaceutical analysis
Devin M. Makey, Brandon T. Ruotolo
Expert Review of Proteomics (2024) Vol. 21, Iss. 5-6, pp. 259-270
Closed 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
Deep learning-based design and experimental validation of a medicine-like human antibody library
Nandhini Rajagopal, Udit Choudhary, Kenny Tsang, et al.
Briefings in Bioinformatics (2024) Vol. 26, Iss. 1
Open Access
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