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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:

PepNN: a deep attention model for the identification of peptide binding sites
Osama Abdin, Satra Nim, Han Wen, et al.
Communications Biology (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 52

Showing 1-25 of 52 citing articles:

Leveraging machine learning models for peptide–protein interaction prediction
Yin Song, Xuenan Mi, Diwakar Shukla
RSC Chemical Biology (2024) Vol. 5, Iss. 5, pp. 401-417
Open Access | Times Cited: 21
De novo design of peptide binders to conformationally diverse targets with contrastive language modeling
Suhaas Bhat, Kalyan Palepu, Lauren Hong, et al.
Science Advances (2025) Vol. 11, Iss. 4
Closed Access | Times Cited: 7
Characterizing the interaction conformation between T-cell receptors and epitopes with deep learning
Xingang Peng, Yipin Lei, Peiyuan Feng, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 4, pp. 395-407
Closed Access | Times Cited: 33
Genome-scale annotation of protein binding sites via language model and geometric deep learning
Qianmu Yuan, Chong Tian, Yuedong Yang
eLife (2024) Vol. 13
Open Access | Times Cited: 12
GPSFun: geometry-aware protein sequence function predictions with language models
Qianmu Yuan, Chong Tian, Yidong Song, et al.
Nucleic Acids Research (2024) Vol. 52, Iss. W1, pp. W248-W255
Open Access | Times Cited: 9
Comprehensive discovery and functional characterization of the noncanonical proteome
Chengyu Shi, Fangzhou Liu, Xinwan Su, et al.
Cell Research (2025)
Open Access | Times Cited: 1
Artificial Intelligence Technology Assists Enzyme Prediction and Rational Design
Yuhang Wang, SangEun Han, Yi Wang, et al.
Journal of Agricultural and Food Chemistry (2025)
Closed Access | Times Cited: 1
Deep-ProBind: binding protein prediction with transformer-based deep learning model
Salman Khan, Sumaiya Noor, Hamid Hussain Awan, et al.
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access | Times Cited: 1
Protein–DNA binding sites prediction based on pre-trained protein language model and contrastive learning
Yufan Liu, Boxue Tian
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 21
Deepro-Glu: combination of convolutional neural network and Bi-LSTM models using ProtBert and handcrafted features to identify lysine glutarylation sites
Xiao Wang, Zhaoyuan Ding, Rong Wang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 18
De NovoDesign of Peptide Binders to Conformationally Diverse Targets with Contrastive Language Modeling
Suhaas Bhat, Kalyan Palepu, Lauren Hong, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 15
Quantitative approaches for decoding the specificity of the human T cell repertoire
Zahra S. Ghoreyshi, Jason T. George
Frontiers in Immunology (2023) Vol. 14
Open Access | Times Cited: 15
PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features
Abel Chandra, Alok Sharma, Abdollah Dehzangi, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 13
Accurately identifying nucleic-acid-binding sites through geometric graph learning on language model predicted structures
Yidong Song, Qianmu Yuan, Huijun Zhao, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 6
Open Access | Times Cited: 12
moPPIt:De NovoGeneration of Motif-Specific Binders with Protein Language Models
Tong Chen, Yinuo Zhang, Pranam Chatterjee
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 4
Artificial intelligence in food bioactive peptides screening: Recent advances and future prospects
Ji Yoon Chang, Haitao Wang, Wentao Su, et al.
Trends in Food Science & Technology (2024), pp. 104845-104845
Closed Access | Times Cited: 4
Artificial intelligence in peptide-based drug design
Silong Zhai, Tiantao Liu, Shaolong Lin, et al.
Drug Discovery Today (2025), pp. 104300-104300
Closed Access
CSpredR: A Multi-Site mRNA Subcellular Localization Prediction Method Based on Fusion Encoding and Hybrid Neural Networks
Xiao Wang, Wenshuai Suo, Rong Wang
Algorithms (2025) Vol. 18, Iss. 2, pp. 67-67
Open Access
Advancements in protein structure prediction: A comparative overview of AlphaFold and its derivatives
Yuktika Malhotra, Jerry R. John, Deepika Yadav, et al.
Computers in Biology and Medicine (2025) Vol. 188, pp. 109842-109842
Closed Access
Machine and deep learning to predict viral fusion peptides
Ana Marta Sequeira, Miguel Rocha, Diana Lousa
Computational and Structural Biotechnology Journal (2025) Vol. 27, pp. 692-704
Open Access
Protein language models for predicting drug–target interactions: Novel approaches, emerging methods, and future directions
Atabey Ünlü, Erva Ulusoy, Melih Gökay Yiğit, et al.
Current Opinion in Structural Biology (2025) Vol. 91, pp. 103017-103017
Closed Access
UMPPI: Unveiling Multilevel Protein–Peptide Interaction Prediction via Language Models
Shuwen Xiong, Jiajie Cai, Hua Shi, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Integrating Structural Information: Comparing Classification-Based and Segmentation-Based Predictors in Bioinformatics (Case Study: Protein-Peptide Region Residue-Level Interaction) Using Structural Information
Shima Shafiee, Abdolhossein Fathi, Faezeh Safari
(2025), pp. 1-7
Closed Access
Structure-Directed Pan-Specific T-Cell Receptor–Peptide-Major Histocompatibility Complex Interaction Prediction
Lijuan Gao, Yumeng Zhang, Fang Ge, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Beyond sequence: Structure-based machine learning
Janani Durairaj, Dick de Ridder, Aalt D. J. van Dijk
Computational and Structural Biotechnology Journal (2022) Vol. 21, pp. 630-643
Open Access | Times Cited: 16
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