Silvia Shen
Thesis title: Harnessing genome characterisation to uncover disease mechanisms
PhD supervisors:
Background
MMathPhil Mathematics and Philosopy, University of Oxford, 2021.
Github account: https://github.com/shensilv
Research summary
My project is researching the genetic architecture of Atopic Dermatitis. I am supervised by Dr Sara Knott, Dr Pau Navarro and Prof Sara Brown from the Centre for Genetic and Experimental Medicine. I am interested in the following research themes:
1) Genome-wide functional enrichment - together with MSc student YuanHao Li, we have developed a method and package for very fast permutation sampling on big genomic datasets. Check out FASTperm here:
2) Discovering core genes as drug targets - with collaborators at the Usher Institute and the MRC Integrative Epidemiology Unit in Bristol, we are working under the omnigenic hypothesis to identify 'core genes' driving Atopic Dermatitis, using data and resources funded by the EU-Horizon BIOMAP project. Check it out here: https://github.com/shensilv/AD-GATE
3) Heritability of AD - current estimates of the heritability of AD are based on twin studies or summary statistics. I am estimating the heritability using genotype data to find out more about the inheritance of AD, as well as the distribution of effect sizes and the polygenicity.
Current research interests
Statistical genetics, computational genetics, population genetics, dermatology, inflammatory disease, immune-mediated disease.Past research interests
Epidemiological modelling (see 'publications'), specifically using differential equations and stochastic models to estimate probabilities of major outbreaks of disease.Affiliated research centres
Lovell-Read, Francesca A., Shen, Silvia, Thompson, Robin. “Estimating Local Outbreak Risks and the Effects of Non-Pharmaceutical Interventions in Age-Structured Populations: SARS-COV-2 as a Case Study.” Journal of Theoretical Biology, 2021, p. 110983., https://doi.org/10.1016/j.jtbi.2021.110983.