Approved Research

Multi-task automated network-centered deep learning to derive mechanisms of longevity and interventions for the extension of healthspan and lifespan

Lay summary

Understanding the mechanisms of Exceptional Longevity (EL) can help guide the development of novel disease-protective interventions. Despite the steady rise in the number of methods to analyze and extract knowledge from these multi-omic biological datasets, the lack of mechanistic insight has prevented development of successful longevity-promoting interventions. Hence, there remains a critical need to develop computational tools to enable the discovery of disease-protective mechanisms and the identification of longevity-promoting interventions. To address this, we propose developing an automated computational framework which utilizes Artificial Intelligence/Machine Learning (AI/ML) to identify causal associations between biomarkers and the EL phenotype in three years.