My research is in the field of bioinformatics and computational biology – the application of computational techniques to the fields of biology, medicine and immunology.

Bioinformatics

My current primary interest is in bioinformatics; in particular, using data analysis techniques to study the development of human immune cells and the differences between development pathways in health and in disease using genomic datasets generated from technologies such as CITE-seq. This work has involved exploration of transcriptomics, proteomics, RNA velocity and VDJ B cell repetoires, and uses existing software libraries such as Seurat, Bioconductor packages, Immcantation and others.

I am also interested in spatial analysis, using technologies such as Imaging Mass Cytometry and Spatial Transcriptomics to assess celluar locations in tissue and cell-cell interactions. This analysis has utilised software such as Seurat, BayesSpace, imcRTools, Ilastik, CellProfiler and more.

Mechanistic modelling

Research into human diseases such as tuberculosis is constrained by the lack of suitable models: no animal models can completely mimic the pathophysiological conditions seen within a human, and laboratory tests are incapable of including the complete environment seen within the host. In silico within-host mechanistic models aim to address this by creating a complete synthetic abstraction of the environment within the host in order to simulate the dynamics of an infection and thus shed light on the complex processes and the factors which influence disease outcomes.

My previous work in this field (see Publications for more details) has involved the study of tuberculosis within the human lung, investigating how differentials in the environmental conditions within the lung affect the progression of disease, using computational metapopulation models and sensitivity analyses frameworks written by me in Python.