iGly-IDN: Identifying Lysine Glycation Sites in Proteins Based on Improved DenseNet-Reference-Cited by-同舟云学术

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iGly-IDN: Identifying Lysine Glycation Sites in Proteins Based on Improved DenseNet

Published:2023-11-28 Issue: Volume: Page:
ISSN:1557-8666
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Jia Jianhua¹,Wu Genqiang¹²^ORCID,Li Meifang³

Affiliation:

1. School of Information Engineering, Jingdezhen Ceramic University, Jingdezhen, China.

2. College of Modern Economics and Management, Jiangxi University of Finance and Economics, Nanchang, China.

3. School of Computer Information Engineering, Nanchang Institute of Technology, Nanchang, China.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation

Link

https://www.liebertpub.com/doi/pdf/10.1089/cmb.2023.0112

Reference61 articles.

1. Degradation products of proteins damaged by glycation, oxidation and nitration in clinical type 1 diabetes

2. PTG-PLM: Predicting Post-Translational Glycosylation and Glycation Sites Using Protein Language Models and Deep Learning

3. LIBSVM

4. XGBoost

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Addressing the problem of lysine glycation prediction in proteins via Recurrent Neural Networks;2024-08-12

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