Developing interpretable machine learning models to gain insight into the relationship between metabolic health and lifestyle
Lead Research Organisation:
University of Oxford
Department Name: Interdisciplinary Bioscience DTP
Abstract
Throughout our lives metabolic processes are constantly occurring and adapting to keep us alive. This invisible force is powered by the food we consume and the air we breathe and works tirelessly to maintain balance within our body. Issues in these processes can silently accumulate as your body battles to maintain metabolic health and many diseases result from these processes falling out of balance. It has been long known that lifestyle factors such a level of physical activity have a positive impact on metabolic health. However, their exact mechanism is not well understood. This research aims to demystify this relationship and thus help improve metabolic health outcomes. By revealing mechanisms behind physical activities impact on metabolic control and identifying biomarkers for exercise adaptation, this research addresses issues of lifespan and healthy aging that fall within the BBSRC Bioscience for Health priority area.
Organisations
People |
ORCID iD |
Peter Minary (Primary Supervisor) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
BB/T008784/1 | 30/09/2020 | 29/09/2028 | |||
2446529 | Studentship | BB/T008784/1 | 30/09/2020 | 29/09/2024 |