iKcr-DRC: prediction of lysine crotonylation sites in proteins based on a novel attention module and DenseNet
The proposed iKcr-DRC model provides an effective and innovative approach for predicting lysine crotonylation sites. It holds great potential for advancing applications in bioinformatics and enhancing the understanding of protein post-translational modifications. An online prediction tool based on the iKcr-DRC model is freely accessible at: http://www.lzzzlab.top/ikcr/.
Authors
- Muhammad Akmal Remli
- Xin Wei (ORCID: https://orcid.org/0000-0002-9720-6771)
- Siqin Hu (ORCID: https://orcid.org/0000-0001-9923-0735)
- Jian Cheng Tu
Institutions
- Beijing Institute of Fashion Technology (CN)
- Universiti Malaysia Kelantan (MY)
Publication Details
- Journal
- Frontiers in Genetics
- Published
- 2025-06-11
- DOI
- https://doi.org/10.3389/fgene.2025.1574832
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangxi Province
- Education Department of Jiangxi Province