Name: Amelie Fritz
Project Title: Bayesian Analysis of Childhood Asthma
Group: BMEM
Supervisor(s): Anders Gorm Pedersen, Klaus Bønnelykke
Project Description:
The main object of this project is to develop Bayesian and Machine Learning approaches to identify (interacting) single nuclear variants (SNPs) associated with paediatric asthma.
Perspective:
Asthma is a common inflammatory disease of the airways. The estimated heredity of asthma is between 70% and 90%, indicating that genetic factors play a major role in disease development. Despite the high heredity of asthma, only a limited number of associated genes have been verified in genome-wide association studies (GWAS), and these only explain a small proportion of the disease variance observed between individuals, a phenomenon delineated as "missing heritability".