Co-Expression Network and Machine Learning Analysis of Transcriptomics Data Identifies Distinct Gene Signatures and Pathways in Lesional and Non-Lesional Atopic Dermatitis
Differential gene expression, co-expression networks and ML analyses of pathway expression have unveiled relevant pathways and gene signatures that distinguish between lesional, non-lesional, and healthy skin, providing valuable insights into AD pathogenesis.
Authors
- Tesfaye B. Mersha (ORCID: https://orcid.org/0000-0002-9189-8447)
- Lili Ding (ORCID: https://orcid.org/0000-0003-2345-3726)
- Latha Satish
- Eskezeia Y. Dessie (ORCID: https://orcid.org/0000-0001-9194-5816)
Institutions
- Cincinnati Children's Hospital Medical Center (US)
- University of Cincinnati (US)
Publication Details
- Journal
- Journal of Personalized Medicine
- Published
- 2024-09-10
- DOI
- https://doi.org/10.3390/jpm14090960
- Citations
- 3
- Primary Topic
- Dermatology and Skin Diseases
- Type
- article
- Field-Weighted Citation Impact
- 1.60
Funders
- National Institutes of Health
- National Human Genome Research Institute