I am a computational biologist at Manchester Cancer Research Centre where I work with David Wedge in the field of Cancer Genomics and Data Science. My work focuses on applying machine learning and statistical techniques to make novel discoveries across a wide range of cancer types.

Currently, I work within multiple clinical interpretation partnerships (GeCIPS) of the UK’s 100,000 genomes project, analysing data from Whole Genome Sequencing (WGS) experiments to identify genomic features that drive tumour evolution, with my focus on ovarian and endometrial cancers.

Prior to joining Wedge Lab, I worked within the Systems and Synthetic Biology field developing metabolic models in plants and bacteria. My experience includes developing a genome-scale constraints-based model of tomato ripening and assessing its flux distributions at different phases and developing kinetic models of engineered monoterpene pathways and systematically interrogating them using a novel ensemble modelling approach. I built models to investigate the potential of improving the production of industrially attractive secondary metabolite compounds.

My goal is to develop and master a wide range of bioinformatics tools and data science skills and techniques across different omics types.