Nina Billows is a PhD student at the Royal Veterinary College, London. Her research aims to improve the characterisation of drug-resistance mutations in Mycobacterium tuberculosis, the causative agent of Tuberculosis (TB), using bioinformatic and machine learning approaches. Prior to her PhD, Nina completed her MSc in Tropical Disease Biology at Liverpool School of Tropical Medicine and her undergraduate degree in Biological Sciences from University of Oxford. Her other research interests include infectious disease genomics, big data, and machine learning.
Tuberculosis (TB) is caused by the bacterium Mycobacterium tuberculosis and was the second leading infectious killer in 2020. Although TB can successfully be treated using antibiotics, its control is hindered by the development of drug-resistant strains. Nina’s research focusses on the prediction of drug-resistant phenotypes from genomic variants in Mycobacterium tuberculosis whole genome sequences with a view to improve genomic surveillance and clinical decision making. During her placement at The Alan Turing Institute, Nina aims to use multilabel machine learning classifiers to predict drug susceptibility phenotypes across a panel of drugs simultaneously. To accomplish this Nina will explore methods to address existing limitations of multilabel classification including missing data imputation and model interpretability.