Innovative approaches to analyse high-dimensional omics data

Since my PhD I have been working on large-scale omics data, mainly in transcriptomics but I am also keen to expand into other types of high-dimensional biological datasets.

Some of my key works in the area:

• We used bulk transcriptomics data to analyse the distinct function involvement of different APOBEC3 cytidine deaminase family members in cancer and immunity (Nucleic Acids Research 2019)
• Together with our collaborators we generated and annotated one of the first single-cell RNA sequencing (scRNA-seq) atlas of B cells from peripheral blood which remains well-utilised to this date (Frontiers in Immunology 2021)
• We created sciCSR that extracts B cell specific biological signals from scRNA-seq alignments and use this to understand the dynamics of B cell maturation (Nature Methods 2024)

I am keen to explore a wide variety of biological systems beyond B cells. We are also exploring new methods and strategies to characterise and understand Artificial Intelligence methods developed in this area, to understand how these approaches learn novel biology from noisy, complex measurements of molecular outputs of cells.