Machine learning and burden analyses highlight novel candidate genes in Parkinson's disease
Sitki Cem Parlar, Eric Yu, Sajanth Kanagasingam, Zhao Zhang, Lang Liu, Morvarid Ghamgosar Shahkhali, Cloe Chantereault, Nathan C. Karpilovsky, Donovan Worrall, Rhalena A. Thomas, Konstantin A. Senkevich, Edward A. Fon, Ziv Gan‐Or
The paper integrates machine learning and rare variant burden analysis to identify novel candidate genes for Parkinson's disease.
medRxiv · Feb 11, 2026 · PreprintGenetic & Genomic Medicine