Computational Biology Team
We use computational and mathematical approaches to study the biological mechanisms that drive disease.
The computational biology group is focused on utilising computational, mathematical and systems biology approaches as tools to understand how biological systems work across a broad spectrum of musculoskeletal and inflammatory diseases. We have active projects on multiple myeloma bone cancer, mesenchymal stem cell differentiation, ageing, inflammatory arthritis, preeclampsia and uterine fibroids. This research builds upon strong collaborations between clinicians, hospitals, industry and wet-lab scientists.
The scientific application areas of the group are focused on:
Single cell transcriptional approaches to investigate epigenetic heterogeneity
Epigenetic mechanisms enable functional diversification of cells with identical genomes, and how these processes work is critical to understanding their cellular distinctiveness and function. However, the majority of our current understanding drives from interpreting epigenetic regulation in bulk populations, that may hide the epigenetic variation within cellular populations. In combination with the molecular biology group, we are developing single-cell epigenomic technologies and leveraging this with chemical and knockout screening approaches to overcome our limited understanding of the contribution of these modifications to biology.
Systems biology approaches for drug discovery
Systems biology is the study of biological systems whose behaviour cannot be reduced to the linear sum of their parts. Specifically, we are developing and applying mathematical modelling to explore the genome, epigenome and transcriptome of cells in order to better understand normal development and disease processes. Additionally, in collaboration with the Bayer healthcare alliance, we have been using systems biology to understand the molecular mechanisms underpinning fibroid growth in women with uterine fibroids.
Development of computational pipelines to aid NGS analysis
To facilitate our ongoing wet-lab experiments, we develop computational tools that can be used to gain mechanistic insight into the pathophysiology of disease. As such, we are engaged in the development of computational pipelines that allow the complex analysis of Next-generation sequencing data possible.