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SUMMARY:MuSpAn: A toolbox for Multiscale Spatial Analysis - Joshua Moore (
 University of Oxford)
DTSTART:20250918T093000Z
DTEND:20250918T093500Z
UID:TALK236545@talks.cam.ac.uk
DESCRIPTION:\n\nDigital twins in oncology promise to revolutionize persona
 lised medicine by simulating tumour progression and treatment response at 
 multiple biological scales. A key challenge in realising this vision lies 
 in accurately modelling the spatial organisation of cells within the tumou
 r microenvironment\, a complex and dynamic system that profoundly influenc
 es disease trajectory. Spatial biology provides essential insights into th
 ese cellular ecosystems\, yet the multiscale complexity of mammalian tissu
 es\, and the lack of standardised analytical frameworks\, continues to lim
 it the interpretability and reproducibility of spatial data.\nTo address t
 hese challenges\, we introduce MuSpAn\, a Python-based toolbox for Multisc
 ale Spatial Analysis of spatial data. Designed to support the development 
 of computational models such as digital twins\, MuSpAn offers an imaging t
 echnology-agnostic platform for analysing spatial features from the subcel
 lular to the tissue scale. By integrating mathematical methods from spatia
 l statistics\, network theory\, topological data analysis\, and morphology
 \, MuSpAn enables quantitative\, scalable\, and customisable analysis of s
 patial patterns in healthy and diseased tissues.\nUnlike rigid\, predefine
 d pipelines\, MuSpAn supports both the design of high-throughput automated
  workflows and flexible exploratory analysis\, empowering users to tailor 
 their approach to specific research questions. It also facilitates queryin
 g and integration of diverse spatial elements\, such as point-like cellula
 r coordinates and polygonal tissue regions\, lowering computational barrie
 rs for interdisciplinary teams. Extensive documentation\, tutorials\, and 
 exemplar analyses from published studies (available at www.muspan.co.uk) f
 urther support adoption across the research community. By equipping resear
 chers with robust mathematical tools for spatial data analysis\, MuSpAn co
 ntributes to the foundational infrastructure necessary for building interp
 retable\, data-driven oncological digital twins\, enhancing our capacity t
 o model disease progression and improve clinical outcomes.\n\n
LOCATION:Seminar Room 1\, Newton Institute
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