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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:

Machine learning optimization of candidate antibody yields highly diverse sub-nanomolar affinity antibody libraries
Lin Li, Esther Gupta, John Spaeth, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 37

Showing 1-25 of 37 citing articles:

Prediction of effluent total nitrogen and energy consumption in wastewater treatment plants: Bayesian optimization machine learning methods
Gang Ye, Jinquan Wan, Zhicheng Deng, et al.
Bioresource Technology (2024) Vol. 395, pp. 130361-130361
Closed Access | Times Cited: 17
Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities
Connor D. Flynn, Dingran Chang
Diagnostics (2024) Vol. 14, Iss. 11, pp. 1100-1100
Open Access | Times Cited: 11
Neural network extrapolation to distant regions of the protein fitness landscape
Chase R. Freschlin, Sarah A. Fahlberg, Pete Heinzelman, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 8
Advancing Antibody Engineering through Synthetic Evolution and Machine Learning
Edward B. Irvine, Sai T. Reddy
The Journal of Immunology (2024) Vol. 212, Iss. 2, pp. 235-243
Closed Access | Times Cited: 7
Toward risk analysis of the impact of artificial intelligence on the deliberate biological threat landscape
Matthew E. Walsh
Risk Analysis (2025)
Closed Access
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: 5
The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design
Eugenio Gallo
Journal of Biomedical Science (2024) Vol. 31, Iss. 1
Open Access | Times Cited: 4
Accurate top protein variant discovery via low-N pick-and-validate machine learning
Hoi Yee Chu, John H.C. Fong, Dawn Thean, et al.
Cell Systems (2024) Vol. 15, Iss. 2, pp. 193-203.e6
Closed Access | Times Cited: 3
Recent advances in generative biology for biotherapeutic discovery
Marissa Mock, Christopher J. Langmead, Peter Grandsard, et al.
Trends in Pharmacological Sciences (2024) Vol. 45, Iss. 3, pp. 255-267
Open Access | Times Cited: 3
Applications and challenges in designing VHH-based bispecific antibodies: leveraging machine learning solutions
Michael Mullin, James McClory, Winston Haynes, et al.
mAbs (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 3
AI/ML combined with next-generation sequencing of VHH immune repertoires enables the rapid identification of de novo humanized and sequence-optimized single domain antibodies: a prospective case study
Paul Arras, Han Byul Yoo, Lukas Pekar, et al.
Frontiers in Molecular Biosciences (2023) Vol. 10
Open Access | Times Cited: 8
Nanopore sensing and beyond: Electrochemical systems for optically-coupled single-entity studies, stimulus-responsive gating applications, and point-of-care sensors
Julius Reitemeier, Jarek Metro, Kaiyu Fu
Sensors and Actuators Reports (2024) Vol. 8, pp. 100225-100225
Open Access | Times Cited: 2
Neural network extrapolation to distant regions of the protein fitness landscape
Sarah A. Fahlberg, Chase R. Freschlin, Pete Heinzelman, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 7
BiSpec Pairwise AI: guiding the selection of bispecific antibody target combinations with pairwise learning and GPT augmentation
Xin Zhang, Huiyu Wang, Chunyun Sun
Journal of Cancer Research and Clinical Oncology (2024) Vol. 150, Iss. 5
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
Precision engineering of antibodies: A review of modification and design in the Fab region
Sa A. Wang, Yao Li, Jianfeng Mei, et al.
International Journal of Biological Macromolecules (2024) Vol. 275, pp. 133730-133730
Closed Access | Times Cited: 1
AntiFormer: graph enhanced large language model for binding affinity prediction
Qing Wang, Yuzhou Feng, Yanfei Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 5
Open Access | Times Cited: 1
Development and experimental validation of computational methods for human antibody affinity enhancement
Junxin Li, Linbu Liao, Chao Zhang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access | Times Cited: 1
AIntibody: an experimentally validated in silico antibody discovery design challenge
M. Frank Erasmus, Laura P. Spector, Fortunato Ferrara, et al.
Nature Biotechnology (2024) Vol. 42, Iss. 11, pp. 1637-1642
Open Access | Times Cited: 1
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
Sequence‐based design and construction of synthetic nanobody library
Chuanyong Liu, Yanping Li, Qinghua He, et al.
Biotechnology and Bioengineering (2024) Vol. 121, Iss. 6, pp. 1973-1985
Closed Access
Ion channel inhibition by targeted recruitment of NEDD4-2 with divalent nanobodies
Travis J. Morgenstern, Arden Darko-Boateng, Emmanuel Afriyie, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Likelihood-based fine-tuning of protein language models for few-shot fitness prediction and design
Alex Hawkins‐Hooker, Jakub Kmec, Oliver Bent, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
AI-guided few-shot inverse design of HDP-mimicking polymers against drug-resistant bacteria
Tianyu Wu, Min Zhou, Jingcheng Zou, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access
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