An effective similarity integration multi-modal graph neural network method to facilitate disease gene prioritization (A04)

点击翻译按钮获取中文摘要

We will develop a machine learning approach that improves disease gene discovery by incorporating the similarity of genes and diseases respectively. In a proof-of-principle study, we will make use of a large neurodevelopmental disorder patient cohort, as well as other pediatric genetic disease cohorts. Specifically, we will develop an end-to-end multi-modal graph neural network for disease gene prioritization. This model will be evaluated in the disease cohorts and novel candidate genes will be experimentally confirmed by cell and animal models.