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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:

Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
Paulina Szymczak, Marcin Możejko, Tomasz Grzegorzek, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 85

Showing 1-25 of 85 citing articles:

Cell-free biosynthesis combined with deep learning accelerates de novo-development of antimicrobial peptides
Amir Pandi, David Adam, Amir Zare, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 72
Exploring the Potential of Bioactive Peptides: From Natural Sources to Therapeutics
Kruttika Purohit, Narsimha Reddy, Anwar Sunna
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 3, pp. 1391-1391
Open Access | Times Cited: 46
Antimicrobial resistance crisis: could artificial intelligence be the solution?
Guangyu Liu, Dan Yu, Mei-Mei Fan, et al.
Military Medical Research (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 40
Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides
Montserrat Goles, Anamaria Sanchez–Daza, Gabriel Cabas-Mora, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 4
Open Access | Times Cited: 30
Global marine microbial diversity and its potential in bioprospecting
Jianwei Chen, Yangyang Jia, Ying Sun, et al.
Nature (2024) Vol. 633, Iss. 8029, pp. 371-379
Open Access | Times Cited: 24
Diff-AMP: tailored designed antimicrobial peptide framework with all-in-one generation, identification, prediction and optimization
Rui Wang, Tao Wang, Linlin Zhuo, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 23
A Foundation Model Identifies Broad-Spectrum Antimicrobial Peptides against Drug-Resistant Bacterial Infection
Tingting Li, Xuanbai Ren, Xiaoli Luo, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 17
Artificial intelligence in drug development
Kang Zhang, Xin Yang, Yifei Wang, et al.
Nature Medicine (2025) Vol. 31, Iss. 1, pp. 45-59
Closed Access | Times Cited: 17
Explainable deep learning and virtual evolution identifies antimicrobial peptides with activity against multidrug-resistant human pathogens
Beilun Wang, Peijun Lin, Yi Zhong, et al.
Nature Microbiology (2025)
Closed Access | Times Cited: 7
Artificial intelligence using a latent diffusion model enables the generation of diverse and potent antimicrobial peptides
Y. C. Wang, Minghui Song, Fen Liu, et al.
Science Advances (2025) Vol. 11, Iss. 6
Closed Access | Times Cited: 6
The Role of Artificial Intelligence and Machine Learning in Predicting and Combating Antimicrobial Resistance
Hazrat Bilal, Muhammad Nadeem Khan, Sabir Khan, et al.
Computational and Structural Biotechnology Journal (2025) Vol. 27, pp. 423-439
Open Access | Times Cited: 5
AI Methods for Antimicrobial Peptides: Progress and Challenges
Carlos A. Brizuela, Gary Liu, J Stokes, et al.
Microbial Biotechnology (2025) Vol. 18, Iss. 1
Open Access | Times Cited: 3
Deep learning tools to accelerate antibiotic discovery
Angela Cesaro, Mojtaba Bagheri, Marcelo D. T. Torres, et al.
Expert Opinion on Drug Discovery (2023) Vol. 18, Iss. 11, pp. 1245-1257
Closed Access | Times Cited: 27
AMP-Diffusion: Integrating Latent Diffusion with Protein Language Models for Antimicrobial Peptide Generation
Tianlai Chen, Pranay Vure, Rishab Pulugurta, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 15
Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design
Xinyi Wu, Huitian Lin, Renren Bai, et al.
European Journal of Medicinal Chemistry (2024) Vol. 268, pp. 116262-116262
Closed Access | Times Cited: 13
Development strategies and application of antimicrobial peptides as future alternatives to in-feed antibiotics
Qingping Liang, Zhemin Liu, Ziyu Liang, et al.
The Science of The Total Environment (2024) Vol. 927, pp. 172150-172150
Closed Access | Times Cited: 10
Machine learning and genetic algorithm-guided directed evolution for the development of antimicrobial peptides
Heqian Zhang, Yihan Wang, Yanran Zhu, et al.
Journal of Advanced Research (2024)
Open Access | Times Cited: 9
Harnessing AI for Enhanced Screening of Antimicrobial Bioactive Compounds in Food Safety and Preservation
Mengyue Zhou, Juliana Pinto de Lima, Hefei Zhao, et al.
Trends in Food Science & Technology (2025), pp. 104887-104887
Closed Access | Times Cited: 1
Advance in peptide-based drug development: delivery platforms, therapeutics and vaccines
Wen‐Jing Xiao, Wenjie Jiang, Zheng Chen, et al.
Signal Transduction and Targeted Therapy (2025) Vol. 10, Iss. 1
Open Access | Times Cited: 1
Pre-trained molecular representations enable antimicrobial discovery
Roberto Olayo-Alarcón, Martin K. Amstalden, Annamaria Zannoni, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 1
Perspectives in Searching Antimicrobial Peptides (AMPs) Produced by the Microbiota
Luigui Gallardo-Becerra, Melany Cervantes-Echeverría, Fernanda Cornejo‐Granados, et al.
Microbial Ecology (2023) Vol. 87, Iss. 1
Open Access | Times Cited: 20
Accelerating the Discovery and Design of Antimicrobial Peptides with Artificial Intelligence
Mariana del Carmen Aguilera‐Puga, Natalia L. Cancelarich, Mariela M. Marani, et al.
Methods in molecular biology (2023), pp. 329-352
Closed Access | Times Cited: 19
Artificial intelligence-driven antimicrobial peptide discovery
Paulina Szymczak, Ewa Szczurek
Current Opinion in Structural Biology (2023) Vol. 83, pp. 102733-102733
Open Access | Times Cited: 18
The limits of prediction: Why intrinsically disordered regions challenge our understanding of antimicrobial peptides
Roberto Bello‐Madruga, Marc Torrent
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 972-981
Open Access | Times Cited: 7
Antimicrobial Peptides: Potential Alternative to Antibiotics and Overcoming Limitations for Future Therapeutic Applications
Vrushali Somase, Sharav Desai, Vipul Patel, et al.
International Journal of Peptide Research and Therapeutics (2024) Vol. 30, Iss. 4
Closed Access | Times Cited: 7
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