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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:

AntiBP3: A Method for Predicting Antibacterial Peptides against Gram-Positive/Negative/Variable Bacteria
Nisha Bajiya, Shubham Choudhury, Anjali Dhall, et al.
Antibiotics (2024) Vol. 13, Iss. 2, pp. 168-168
Open Access | Times Cited: 10

Showing 10 citing articles:

AMPActiPred: A three‐stage framework for predicting antibacterial peptides and activity levels with deep forest
Lantian Yao, Jiahui Guan, Peilin Xie, et al.
Protein Science (2024) Vol. 33, Iss. 6
Closed Access | Times Cited: 10
THPdb2: compilation of FDA approved therapeutic peptides and proteins
Shipra Jain, Srijanee Gupta, Sumeet Patiyal, et al.
Drug Discovery Today (2024) Vol. 29, Iss. 7, pp. 104047-104047
Closed Access | Times Cited: 6
Perturbation-Theory Machine Learning for Multi-Objective Antibacterial Discovery: Current Status and Future Perspectives
Valeria V. Kleandrova, M. Natália D. S. Cordeiro, Alejandro Speck‐Planche
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1166-1166
Open Access
Prediction of inhibitory peptides against E.coli with desired MIC value
Nisha Bajiya, Nishant Kumar, Gajendra P. S. Raghava
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Protein Language Models and Machine Learning Facilitate the Identification of Antimicrobial Peptides
David Medina-Ortiz, Sebastián Contreras, Diego Fernández, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 16, pp. 8851-8851
Open Access | Times Cited: 3
Prediction of inhibitory peptides against E. coli with desired MIC value
Nisha Bajiya, Nishant Kumar, Gajendra P. S. Raghava
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Closed Access
Machine Learning Tools for Peptide Bioactivity Evaluation – Implications for Cell Culture Media Optimization and the Broader Cultivated Meat Industry
Kathy Sharon Isaac, Michelle Combe, Greg Potter, et al.
Current Research in Food Science (2024) Vol. 9, pp. 100842-100842
Open Access
Computational Prediction and Structural Analysis of α-Hairpinins, a Ubiquitous Family of Antimicrobial Peptides, Using the Cysmotif Searcher Pipeline
Anna A. Slavokhotova, Andrey Shelenkov, Е. А. Рогожин
Antibiotics (2024) Vol. 13, Iss. 11, pp. 1019-1019
Open Access
Database, prediction, and antibacterial research of astringency based on large language models
一彦 須賀, Yilin Gao, Kaifeng Liu, et al.
Computers in Biology and Medicine (2024) Vol. 184, pp. 109375-109375
Closed Access
AISMPred: A Machine Learning Approach for Predicting Anti-Inflammatory Small Molecules
Subathra Selvam, Priya Dharshini Balaji, Honglae Sohn, et al.
Pharmaceuticals (2024) Vol. 17, Iss. 12, pp. 1693-1693
Open Access
Accelerating antimicrobial peptide design: Leveraging deep learning for rapid discovery
Ahmad Al-Omari, Yazan H. Akkam, Ala’a Zyout, et al.
PLoS ONE (2024) Vol. 19, Iss. 12, pp. e0315477-e0315477
Open Access
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