Amber is PhD researcher at the University of Leeds in the field of computational biology. She is interested in applying statistics and machine learning techniques to genome-wide sequencing datasets, to predict how genes are regulated in development and disease. Prior to her doctoral training, Amber received a BSc in Genetics from the University of Liverpool.
Amber is interested in how gene regulatory networks are rewired in cellular differentiation and disease. As a computational biologist, she tackles this problem by integrating genome-wide ‘omics datasets using methods from statistics and machine learning. In her PhD work, Amber has created predictive models of gene expression control in B lymphocyte white blood cells during the immune response. She is now exploring how mutations in regulatory DNA contribute to autoimmune diseases and blood cancers, through statistical analysis of whole genome sequence data.