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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:

Mini-review: Recent advances in post-translational modification site prediction based on deep learning
Lingkuan Meng, Wai‐Sum Chan, Lei Huang, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 3522-3532
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model
Pawel Pratyush, Suresh Pokharel, Hiroto Saigo, et al.
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 16
TransPTM: a transformer-based model for non-histone acetylation site prediction
Lingkuan Meng, Xingjian Chen, Ke Cheng, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 7
Post-translational modification prediction via prompt-based fine-tuning of a GPT-2 model
Palistha Shrestha, Jeevan Kandel, Hilal Tayara, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 6
Construction of machine learning diagnostic models for cardiovascular pan-disease based on blood routine and biochemical detection data
Zhicheng Wang, Ying Gu, Lindan Huang, et al.
Cardiovascular Diabetology (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 6
Analysis and review of techniques and tools based on machine learning and deep learning for prediction of lysine malonylation sites in protein sequences
Shahin Ramazi, Seyed Amir Hossein Tabatabaei, Elham Khalili, et al.
Database (2024) Vol. 2024
Open Access | Times Cited: 5
PhosAF: An integrated deep learning architecture for predicting protein phosphorylation sites with AlphaFold2 predicted structures
Ziyuan Yu, Jialin Yu, Hongmei Wang, et al.
Analytical Biochemistry (2024) Vol. 690, pp. 115510-115510
Closed Access | Times Cited: 5
Mechanisms of Autophagy in Ineffective Reperfusion After Ischemic Stroke
Shangying Bai, Yuchuan Ding, Leticia Simo, et al.
Journal of Neuroscience Research (2025) Vol. 103, Iss. 1
Closed Access
DLBWE-Cys: a deep-learning-based tool for identifying cysteine S-carboxyethylation sites using binary-weight encoding
Zhengtao Luo, Qingyong Wang, Yingchun Xia, et al.
Frontiers in Genetics (2025) Vol. 15
Open Access
IL-33/ST2 axis in diverse diseases: regulatory mechanisms and therapeutic potential
Feiya Sheng, Li Mi, Jia-Mei Yu, et al.
Frontiers in Immunology (2025) Vol. 16
Open Access
SUMO-LMNet: Lossless Mapping Network for Predicting SUMOylation Sites in SUMO1 and SUMO2 using High-Dimensional Features
Cheng‐Hsun Ho, Yen-Wei Chu, Lan-Ying Huang, et al.
Computational and Structural Biotechnology Journal (2025) Vol. 27, pp. 1048-1059
Open Access
Deep Learning Techniques Applied to Phosphorylation Site Prediction: A Systematic Review
Antônio Carlos da Silva Júnior, André Massahiro Shimaoka, Luciano Rodrigo Lopes, et al.
SN Computer Science (2025) Vol. 6, Iss. 4
Closed Access
Protein phosphorylation database and prediction tools
Mingxiao Zhao, Qiang Chen, Fulai Li, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 12
Post‐translational modifications of proteins in cardiovascular diseases examined by proteomic approaches
Miroslava Št́astná
FEBS Journal (2024)
Open Access | Times Cited: 3
New Histone Lysine Acylation Biomarkers and Their Roles in Epigenetic Regulation
Qianyun Fu, Amber Cat, Y. George Zheng
Current Protocols (2023) Vol. 3, Iss. 4
Open Access | Times Cited: 7
Deep Learning in Phosphoproteomics: Methods and Application in Cancer Drug Discovery
Neha Varshney, Abhinava K. Mishra
Proteomes (2023) Vol. 11, Iss. 2, pp. 16-16
Open Access | Times Cited: 7
Emerging trends in post-translational modification: Shedding light on Glioblastoma multiforme
Smita Kumari, Rohan Gupta, Rashmi K. Ambasta, et al.
Biochimica et Biophysica Acta (BBA) - Reviews on Cancer (2023) Vol. 1878, Iss. 6, pp. 188999-188999
Closed Access | Times Cited: 7
Pathological Impact of Redox Post-Translational Modifications
Charbel Chahla, Hervé Kovacic, Lotfi Ferhat, et al.
Antioxidants and Redox Signaling (2024) Vol. 41, Iss. 1-3, pp. 152-180
Closed Access | Times Cited: 2
Nphos: Database and Predictor of Protein N-phosphorylation
Mingxiao Zhao, Ruofan Ding, Qiang Chen, et al.
Genomics Proteomics & Bioinformatics (2024) Vol. 22, Iss. 3
Open Access | Times Cited: 1
DeepO-GlcNAc: a web server for prediction of protein O-GlcNAcylation sites using deep learning combined with attention mechanism
Liyuan Zhang, Tingzhi Deng, Shuijing Pan, et al.
Frontiers in Cell and Developmental Biology (2024) Vol. 12
Open Access | Times Cited: 1
Unpacking the complexity of nuclear IL-33 (nIL-33): a crucial regulator of transcription and signal transduction
Zengbin Wang, Nanhong Tang
Journal of Cell Communication and Signaling (2023) Vol. 17, Iss. 4, pp. 1131-1143
Open Access | Times Cited: 4
PhosBoost: Improved phosphorylation prediction recall using gradient boosting and protein language models
Elly Poretsky, Carson M. Andorf, Taner Z. Sen
Plant Direct (2023) Vol. 7, Iss. 12
Open Access | Times Cited: 4
Artificial Intelligence Transforming Post-Translational Modification Research
Doo Nam Kim, Tianzhixi Yin, Tong Zhang, et al.
Bioengineering (2024) Vol. 12, Iss. 1, pp. 26-26
Open Access | Times Cited: 1
TransPTM: a Transformer-Based Model for Non-Histone Acetylation Site Prediction
Lingkuan Meng, Xingjian Chen, Ke Cheng, et al.
(2023)
Open Access | Times Cited: 2
Substrate Prediction for RiPP Biosynthetic Enzymes via Masked Language Modeling and Transfer Learning
Joseph D. Clark, Xuenan Mi, Douglas A. Mitchell, et al.
Digital Discovery (2024)
Open Access
Machine learning-based exploration of enzyme-substrate networks: SET8-mediated methyllysine and its changing impact within cancer proteomes
Kyle K. Biggar, Nashira H Ridgeway, Anand Chopra, et al.
Research Square (Research Square) (2024)
Open Access
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