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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:

iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities
Jing Xu, Fuyi Li, Chen Li, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Open Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

A Transformer-Based Ensemble Framework for the Prediction of Protein–Protein Interaction Sites
Minjie Mou, Ziqi Pan, Zhimeng Zhou, et al.
Research (2023) Vol. 6
Open Access | Times Cited: 49
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: 20
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
H2Opred: a robust and efficient hybrid deep learning model for predicting 2’-O-methylation sites in human RNA
Nhat Truong Pham, Rajan Rakkiyapan, Jongsun Park, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 21
Prediction of blood–brain barrier penetrating peptides based on data augmentation with Augur
Zhi-Feng Gu, Yu-Duo Hao, Tianyu Wang, et al.
BMC Biology (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 11
mACPpred 2.0: Stacked Deep Learning for Anticancer Peptide Prediction with Integrated Spatial and Probabilistic Feature Representations
Vinoth Kumar Sangaraju, Nhat Truong Pham, Leyi Wei, et al.
Journal of Molecular Biology (2024) Vol. 436, Iss. 17, pp. 168687-168687
Closed Access | Times Cited: 8
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
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: 19
UniproLcad: Accurate Identification of Antimicrobial Peptide by Fusing Multiple Pre-Trained Protein Language Models
Xiao Wang, Wu Zhou, Rong Wang, et al.
Symmetry (2024) Vol. 16, Iss. 4, pp. 464-464
Open Access | Times Cited: 6
PepNet: an interpretable neural network for anti-inflammatory and antimicrobial peptides prediction using a pre-trained protein language model
Jiyun Han, Tongxin Kong, Juntao Liu
Communications Biology (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 6
Therapeutic Peptide Development Revolutionized: Harnessing the Power of Artificial Intelligence for Drug Discovery
Samaneh Hashemi, Parisa Vosough, Saeed Taghizadeh, et al.
Heliyon (2024) Vol. 10, Iss. 22, pp. e40265-e40265
Open Access | Times Cited: 6
Superficial Fungal Infections and Artificial Intelligence: A Review on Current Advances and Opportunities: REVISION
Bahareh Hasan Pour
Mycoses (2025) Vol. 68, Iss. 1
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
Unlocking the Potential of Antimicrobial Peptides: Cutting-Edge Advances and Therapeutic Potential in Combating Bacterial Keratitis
Bingjia Xiao, Jie Wang, Jie Xing, et al.
Bioconjugate Chemistry (2025)
Closed Access
Designing a Novel Ultrashort Cyclic [R3W4V] Antimicrobial Peptide with Superior Antimicrobial Potential Based on the Transmembrane Structure to Facilitate Pore Formation
Lei Liu, Zhihong Shi, Mingqiong Tong, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Peptide classification landscape: An in-depth systematic literature review on peptide types, databases, datasets, predictors architectures and performance
Muhammad Nabeel Asim, Tayyaba Asif, Faiza Mehmood, et al.
Computers in Biology and Medicine (2025) Vol. 188, pp. 109821-109821
Closed Access
Leveraging protein language models for robust antimicrobial peptide detection
Lichao Zhang, Shuwen Xiong, Lei Xu, et al.
Methods (2025)
Closed Access
Anti-BioEn: An advanced framework for accurate bioactive agent classification based on hybrid models and graph feature encoding method
Shazzad Hossain Shaon, Farooq Sultan, Tasmin Karim, et al.
BIO Web of Conferences (2025) Vol. 163, pp. 01007-01007
Open Access
Discovery of antimicrobial peptides from Bacillus genomes against phytopathogens with deep learning models
Huan Su, Mengli Gu, Zechao Qu, et al.
Chemical and Biological Technologies in Agriculture (2025) Vol. 12, Iss. 1
Open Access
ANNprob-ACPs: A novel anticancer peptide identifier based on probabilistic feature fusion approach
Tasmin Karim, Md. Shazzad Hossain Shaon, Md. Fahim Sultan, et al.
Computers in Biology and Medicine (2023) Vol. 169, pp. 107915-107915
Closed Access | Times Cited: 12
AMP-RNNpro: a two-stage approach for identification of antimicrobials using probabilistic features
Md. Shazzad Hossain Shaon, Tasmin Karim, Md. Fahim Sultan, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
DMAMP: A deep-learning model for detecting antimicrobial peptides and their multi-activities
Qiaozhen Meng, Genlang Chen, Bin Lin, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024) Vol. 21, Iss. 6, pp. 2025-2034
Closed Access | Times Cited: 3
Tackling the Antimicrobial Resistance “Pandemic” with Machine Learning Tools: A Summary of Available Evidence
Doris Rušić, Marko Kumrić, Ana Šešelja Perišin, et al.
Microorganisms (2024) Vol. 12, Iss. 5, pp. 842-842
Open Access | Times Cited: 2
Regular Consumption of Green Tea as an Element of Diet Therapy in Drug-Induced Liver Injury (DILI)
Anna Winiarska‐Mieczan, Karolina Jachimowicz-Rogowska, Małgorzata Kwiecień, et al.
Nutrients (2024) Vol. 16, Iss. 17, pp. 2837-2837
Open Access | Times Cited: 2
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