Application of Machine Learning approaches to genetic and gene expression data to predict neurodegeneration-related endophenotypes
Lead Research Organisation:
CARDIFF UNIVERSITY
Department Name: School of Medicine
Abstract
The project aims to improve prediction of Alzheimer's disease (AD) and AD-associated endophenotypes using the best available data and machine learning methods, to progress from simplistic exclusive categories to probabilistic and multi-label predictions and employ data-driven approaches to seek novel links between clusters of risk genes and phenotypic variables to generate new insights into aetiologically valid strata.
Organisations
People |
ORCID iD |
| Valentina Escott-Price (Primary Supervisor) | |
| Karen Crawford (Student) |
| Description | Brilliant Club Tutorials in Schools (South Wales) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | Activity is based on delivering a series of tutorials based on my PhD research to secondary school aged children. The aim is to teach pupils from disadvantages backgrounds a novel research area whilst developing their confidence and advertising the subject at university level. |
| Year(s) Of Engagement Activity | 2019,2020 |
| Description | Seren Hub Workshops |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | Delivered two undergraduate level workshops to sixth-form aged students at a local college to broaden their horizons and inform them of a novel research area. |
| Year(s) Of Engagement Activity | 2019 |