0+3.5 iCASE student
Understanding how nearly 2 meters of genomic material is organised inside a single cell is a perplexing challenge. Changes in this organisation and subsequent changes in gene regulatory networks can drive a cell towards an aggressive malignant phenotype. My 3.5-year PhD journey aims to elucidate the differences in gene regulatory networks between patients with responsive and refractory Acute Promyelocytic Leukemia. I will be generating Capture Hi-C, RNA-seq, ChIP-seq and Cut&Run libraries and applying my bioinformatic skills to combine and unravel these large complex datasets.
I completed my MRes in Cancer Informatics at Imperial College London in 2017 working with 2 teams across 2 different projects.
Firstly, in the Department of Surgery & Cancer I worked in the bioinformatics hub, testing and optimising a probabilistic model to identify genomic regions which consistently differ in multiple groups of ChIP-seq samples with the project title: “Identifying epigenetic domains in which cancer cells resemble less differentiated stages in development: Application of a probabilistic model for differential peak density.”
Secondly at the Institute of Cancer Research, I worked in the Breast Cancer Now bioinformatics team. My project aimed to take the Breast Cancer TCGA cohort RNA-sequencing data and characterise the alternative splicing differences across various stratified groups, with the title: “Characterisation of the Alternative Splicing Landscape in Breast Cancer”