James Boyle
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG
PersiST: Robust Identification of Spatially Variable Features in Spatial Omics Datasets via Topological Data Analysis
Boyle J, Hamm G, Williams E, JG Hartman R, Söderburg M, Henry I, Casey M (May 2025)
Academic year 2024/25:
- TA for B5.5 Further Mathematical Biology (MT)
- TA for B5.1 Stochastic Modelling of Biological Processes (HT)
My work is funded by a Magdalen Graduate Scholarship.
I am interested in integrating mathematical modelling and machine learning to develop computational methods for the analysis of biomedical systems.
Mathematical modelling provides us with an interpretable and biologically grounded way of quantitatively analysing biomedical systems, whilst machine learning is capable of picking up on the often extremely complex patterns in biomedical data. My interest is in how these two analysis paradigms intersect, and what can be gained by using both of them together to analyse biomedical systems.