Joshua A. Bull

MuSpAn, a Python library of over 100 spatial methods, quantifies multiscale tissue organisation and maps cancer-associated fibroblast subtypes to distinct immune niches in mouse colorectal tumours.

The paper introduces netPCF, a geometry-aware method for quantifying spatial organisation on complex biological domains, showing its utility in biological applications.

This paper develops an agent-based model to simulate vascular remodelling and its impact on tumour growth and response to radiotherapy, showing that friction forces significantly influence vessel compression and tumour regrowth.

The paper develops spatial descriptors using mathematical tools to analyze cell interactions in colorectal cancer progression and demonstrates their utility in identifying disease-related pathways.

This paper introduces a new spatial statistic, the weighted pair correlation function (wPCF), to analyze spatial and phenotypic heterogeneity in agent-based models and multiplex imaging data.