Predicting protein–protein interactions in microbes associated with cardiovascular diseases using deep denoising autoencoders and evolutionary information
Additionally, we explore the application of DAEPPI in the context of cardiovascular disease, showcasing its potential to uncover significant interactions that could contribute to the understanding of disease mechanisms. Our findings indicate that DAEPPI is a powerful tool for advancing research in proteomics and could play a pivotal role in the identification of novel therapeutic targets in cardiovascular disease.
Authors
- Mei Tang
- Sichang Zhou (ORCID: https://orcid.org/0000-0003-4143-0034)
- Yang Li (ORCID: https://orcid.org/0000-0002-0609-6918)
- Wenhua He (ORCID: https://orcid.org/0000-0002-1697-1448)
- Chaojun Li (ORCID: https://orcid.org/0000-0001-9474-7321)
- Jian Luo
Institutions
- Hefei University of Technology (CN)
- Hunan Normal University (CN)
- Fourth Hospital of Changsha (CN)
Publication Details
- Journal
- Frontiers in Pharmacology
- Published
- 2025-03-11
- DOI
- https://doi.org/10.3389/fphar.2025.1565860
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00