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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:

Integrating transformer and imbalanced multi-label learning to identify antimicrobial peptides and their functional activities
Yuxuan Pang, Lantian Yao, Jingyi Xu, et al.
Bioinformatics (2022) Vol. 38, Iss. 24, pp. 5368-5374
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

UniDL4BioPep: a universal deep learning architecture for binary classification in peptide bioactivity
Zhenjiao Du, Xingjian Ding, Yixiang Xu, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 3
Closed Access | Times Cited: 64
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: 21
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: 2
deep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities
Jun Zhao, Hangcheng Liu, Liang‐I Kang, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access | Times Cited: 1
Leveraging transformers‐based language models in proteome bioinformatics
Nguyen Quoc Khanh Le
PROTEOMICS (2023) Vol. 23, Iss. 23-24
Closed Access | Times Cited: 35
iAMP-Attenpred: a novel antimicrobial peptide predictor based on BERT feature extraction method and CNN-BiLSTM-Attention combination model
Wenxuan Xing, Jie Zhang, Chen Li, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 22
DeepAFP: An effective computational framework for identifying antifungal peptides based on deep learning
Lantian Yao, Yuntian Zhang, Wenshuo Li, et al.
Protein Science (2023) Vol. 32, Iss. 10
Closed Access | Times Cited: 19
Artificial intelligence for the discovery of antimicrobial peptides
Paola Ruiz Puentes, Nicolás Aparicio, Pablo Arbeláez
Elsevier eBooks (2025), pp. 59-79
Closed Access
MSCMamba: Prediction of Antimicrobial Peptide Activity Values by Fusing Multiscale Convolution with Mamba Module
Mingyue He, Yongquan Jiang, Yan Yang, et al.
The Journal of Physical Chemistry B (2025)
Closed Access
Deep Learning for Antimicrobial Peptides: Computational Models and Databases
Xiangrun Zhou, Guixia Liu, Shuyuan Cao, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Exploring the repository of de novo designed bifunctional antimicrobial peptides through deep learning
Ruihan Dong, Rongrong Liu, Ziyu Liu, et al.
(2025)
Open Access
Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning
Ruihan Dong, Rongrong Liu, Ziyu Liu, et al.
eLife (2025) Vol. 13
Open Access
Contrastive learning for enhancing feature extraction in anticancer peptides
Byungjo Lee, Dongkwan Shin
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 3
Multi-label classification and features investigation of antimicrobial peptides with various functional classes
Chia‐Ru Chung, Jhen-Ting Liou, Li-Ching Wu, et al.
iScience (2023) Vol. 26, Iss. 12, pp. 108250-108250
Open Access | Times Cited: 6
SME-MFP: A novel spatiotemporal neural network with multiangle initialization embedding toward multifunctional peptides prediction
Jing Xu, Xiaoli Ruan, Jing Yang, et al.
Computational Biology and Chemistry (2024) Vol. 109, pp. 108033-108033
Closed Access | Times Cited: 1
Discovery of anticancer peptides from natural and generated sequences using deep learning
Jianda Yue, Tingting Li, Jiawei Xu, et al.
International Journal of Biological Macromolecules (2024) Vol. 290, pp. 138880-138880
Closed Access | Times Cited: 1
GR-m6A: Prediction of N6-methyladenosine sites in mammals with molecular graph and residual network
Shi Qiu, Renxin Liu, Ying Liang
Computers in Biology and Medicine (2023) Vol. 163, pp. 107202-107202
Closed Access | Times Cited: 4
AutoPeptideML: A study on how to build more trustworthy peptide bioactivity predictors
Raúl Fernández-Díaz, Rodrigo Cossio-Pérez, Clement Agoni, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
dbAMP 3.0: updated resource of antimicrobial activity and structural annotation of peptides in the post-pandemic era
Lantian Yao, Jiahui Guan, Peilin Xie, et al.
Nucleic Acids Research (2024) Vol. 53, Iss. D1, pp. D364-D376
Open Access
Leveraging large language models for peptide antibiotic design
Changge Guan, Fabiano C. Fernandes, Octávio Luiz Franco, et al.
Cell Reports Physical Science (2024) Vol. 6, Iss. 1, pp. 102359-102359
Open Access
Exploring the repository ofde novodesigned bifunctional antimicrobial peptides through deep learning
Ruihan Dong, Rongrong Liu, Ziyu Liu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Exploring the repository of de novo designed bifunctional antimicrobial peptides through deep learning
Ruihan Dong, Rongrong Liu, Ziyu Liu, et al.
(2024)
Open Access
AI-powered microscopy image analysis for parasitology: integrating human expertise
Ruijun Feng, Sen Li, Yang Zhang
Trends in Parasitology (2024) Vol. 40, Iss. 7, pp. 633-646
Closed Access
Reviewer #3 (Public Review): Exploring the repository of de novo designed bifunctional antimicrobial peptides through deep learning
Ruihan Dong, Rongrong Liu, Ziyu Liu, et al.
(2024)
Open Access
Reviewer #1 (Public Review): Exploring the repository of de novo designed bifunctional antimicrobial peptides through deep learning
Ruihan Dong, Rongrong Liu, Ziyu Liu, et al.
(2024)
Open Access
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