Exploring gene expression heterogeneity in burn wounds through machine learning models: in silico analyses-experimental research
This study not only illuminates the gene expression heterogeneity in burn wounds but also suggests the potential influence of age on this variation. By identifying molecular subtypes of burn injury based on gene expression patterns, these findings may help in developing early diagnostic tools and personalized therapeutic approaches.
Authors
- Reza Salehi (ORCID: https://orcid.org/0000-0001-6793-7293)
- Mohammad Reza Zabihi (ORCID: https://orcid.org/0000-0002-9357-2942)
- Pardis Mehdipour Rabori
- Mohammad Akhoondian (ORCID: https://orcid.org/0000-0002-2539-8751)
- Azadeh Emami (ORCID: https://orcid.org/0000-0002-6107-0139)
- Reza Ataee Disfani
- Hengameh Khosravani
Institutions
- Tarbiat Modares University (IR)
- Iran University of Medical Sciences (IR)
- Tehran University of Medical Sciences (IR)
Publication Details
- Journal
- Annals of Medicine and Surgery
- Published
- 2025-10-08
- DOI
- https://doi.org/10.1097/ms9.0000000000004025
- Primary Topic
- Advanced Computational Techniques in Science and Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00