Effective clinical genome interpretation relies on accurately distinguishing between benign and pathogenic rare variants.Current machine learning-based variant prioritization tools are trained on genome-wide data and ...Effective clinical genome interpretation relies on accurately distinguishing between benign and pathogenic rare variants.Current machine learning-based variant prioritization tools are trained on genome-wide data and often overlook key parameters defining geneedisease relationships.展开更多
基金supported by grants from the Association of Paediatric Oncology and Neuroblastoma ONLUS Naples(grant name:Editor)Italian Association for the Fight against Neuroblastoma(grant name:AlterAction)+1 种基金Italian Association for Cancer Research(grant number:25796)Ministry of Health(grant name:PRIN PNRR 2022 P2022NFCPM).
文摘Effective clinical genome interpretation relies on accurately distinguishing between benign and pathogenic rare variants.Current machine learning-based variant prioritization tools are trained on genome-wide data and often overlook key parameters defining geneedisease relationships.
