ArticleFrontiers in physiology2025
Performance exploration of multi-gene panels of alopecia areata susceptibility and drug-binding targets.
Article in Frontiers in physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Artificial Intelligence in Hair Disorders: A Narrative Review.Dermatology and therapy · 2026Review
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10 authors.
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Abstract
Objective: This study aims to identify potential target genes and therapeutic drugs for alopecia areata (AA). Methods: Utilizing training and testing data, we evaluated multi-gene panels derived from commonly upregulated genes in publicly available AA patient datasets. The functions of these genes in biological processes were analyzed to identify special multi-gene panels that may play crucial roles in AA. Differences in immune cell infiltration between AA patients and healthy controls were assessed using gene set variation analysis (GSVA) and the Wald test. Signature genes were further validated in specific subsets using single-cell RNA sequence data. Finally, molecular docking and molecular dynamics simulation were conducted to evaluate interactions between protein structures encoded by signature genes and the potential new drug candidates. Results: When the cut-off value of log Conclusion: In this study, we screened several key genes associated with immune cells and potential drug-like chemicals that could serve as targeted therapies for AA.
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