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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:

CACPP: A Contrastive Learning-Based Siamese Network to Identify Anticancer Peptides Based on Sequence Only
Xuetong Yang, Junru Jin, Ruheng Wang, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 7, pp. 2807-2816
Closed Access | Times Cited: 19

Showing 19 citing articles:

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: 25
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: 9
Dynamic Visualization of Computer-Aided Peptide Design for Cancer Therapeutics
Dan Hou, Haobin Zhou, Yuting Tang, et al.
Drug Design Development and Therapy (2025) Vol. Volume 19, pp. 1043-1065
Open Access | Times Cited: 1
ADP-Fuse: A novel two-layer machine learning predictor to identify antidiabetic peptides and diabetes types using multiview information
Shaherin Basith, Nhat Truong Pham, Minkyung Song, et al.
Computers in Biology and Medicine (2023) Vol. 165, pp. 107386-107386
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
ACP-ESM: A novel framework for classification of anticancer peptides using protein-oriented transformer approach
Zeynep Hilal Kilimci, Mustafa Yalçın
Artificial Intelligence in Medicine (2024) Vol. 156, pp. 102951-102951
Open Access | Times Cited: 8
Editorial: Machine Learning in Bio-cheminformatics
Kenneth M. Merz, Guo‐Wei Wei, Feng Zhu
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 7, pp. 2125-2128
Closed Access | Times Cited: 5
CELA-MFP: a contrast-enhanced and label-adaptive framework for multi-functional therapeutic peptides prediction
Yitian Fang, Mingshuang Luo, Zhixiang Ren, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 4
Open Access | Times Cited: 5
Efficient prediction of anticancer peptides through deep learning
Abdu Salam, Faizan Ullah, Farhan Amin, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e2171-e2171
Open Access | Times Cited: 4
Bridging machine learning and peptide design for cancer treatment: a comprehensive review
Khosro Rezaee, Hossein Eslami
Artificial Intelligence Review (2025) Vol. 58, Iss. 5
Open Access
A comprehensive review and evaluation of machine learning-based approaches for identifying tumor T cell antigens
Watshara Shoombuatong, Saeed Ahmed, Sakib Mahmud, et al.
Computational Biology and Chemistry (2025), pp. 108440-108440
Closed Access
Integrating Traditional Machine Learning and Deep Learning for Precision Screening of Anticancer Peptides: A Novel Approach for Efficient Drug Discovery
M. Xu, Jiefu Pang, Yangyang Ye, et al.
ACS Omega (2024) Vol. 9, Iss. 14, pp. 16820-16831
Open Access | Times Cited: 3
A Prompt and Contrastive Learning-Based Model for Plant Antimicrobial Peptide Prediction
Zhaojing Qin, Jun Meng, Haibin Li, et al.
Communications in computer and information science (2025), pp. 141-153
Closed Access
pACPs-DNN: Predicting Anticancer peptides using Novel Peptide Transformation into Evolutionary and Structure Matrix-based Images with Self-attention Deep Learning Model
Muhammad Khalil Shahid, Maqsood Hayat, Ali Raza, et al.
Computational Biology and Chemistry (2025), pp. 108441-108441
Closed Access
MetaCGRP is a high-precision meta-model for large-scale identification of CGRP inhibitors using multi-view information
Nalini Schaduangrat, Phisit Khemawoot, Apisada Jiso, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
DiffSeqMol: A Non-Autoregressive Diffusion-Based Approach for Molecular Sequence Generation and Optimization
Zixu Wang, Yangyang Chen, Xiucai Ye
(2023)
Open Access | Times Cited: 2
Prediction of Protein-Coding Small ORFs Based on Supervised Contrastive Learning
Dongting Xie, Xinye Bian, Ziling Wang, et al.
IEEE Access (2024) Vol. 12, pp. 129212-129223
Open Access
TF-BAPred: A Universal Bioactive Peptide Predictor Integrating Multiple Feature Representations
Zhenming Wu, Xiaoyu Guo, Yangyang Sun, et al.
Mathematics (2024) Vol. 12, Iss. 22, pp. 3618-3618
Open Access
DiffSeqMol: A Non-Autoregressive Diffusion-Based Approach for Molecular Sequence Generation and Optimization
Yangyang Chen, Zixu Wang, Xiucai Ye
(2023)
Open Access | Times Cited: 1
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