BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Multiscale modelling of collective behaviour: insights\, challenge
 s\, and future perspectives - William Martinson (University of Oxford)
DTSTART:20230810T150000Z
DTEND:20230810T160000Z
UID:TALK201475@talks.cam.ac.uk
DESCRIPTION:Coordination of large groups occurs throughout biology\, with 
 examples including zebrafish stripe patterning and cell formation of embry
 onic tissues. Mathematical models can help elucidate the individual-level 
 mechanisms dominating these dynamics and thereby provide experimental insi
 ghts. We demonstrate this by creating a model for chick cranial neural cre
 st cell (NCC) migration that tracks each individual. This agent-based mode
 l examines whether the creation of an extracellular matrix (ECM) scaffold 
 via NCC remodelling of an initially punctate structure allows trailing cel
 ls to robustly follow their leaders and form consistent streams. Global se
 nsitivity analyses and simulated gain- and loss-of-function experiments su
 ggest that long-distance migration towards target sites most likely occurs
  when cells at the front specialize in creating ECM fibres and trailing ce
 lls efficiently read these cues though upregulating contact guidance (a pr
 ocess by which cells align along ECM structures). This model therefore pro
 vides testable hypotheses about the NCC microenvironment and its role in i
 nducing cell heterogeneity\, but is computationally expensive to simulate.
  This motivates the second part of the talk\, which describes a computatio
 nal pipeline for developing more analytically tractable continuous models 
 that match ensemble average dynamics of a given individual-level framework
 . Using the illustrative example of zebrafish skin pattern formation\, &nb
 sp\;we use this pipeline to match a continuous and discrete models that ea
 ch describe the movement and proliferation of a single cell population. By
  fitting parameters controlling the time scale of each mechanism\, we show
  how this pipeline can provide accurate descriptions of individual-level d
 ata and highlight the importance of accounting for possible synergistic ef
 fects when multiple mechanisms occur simultaneously.
LOCATION:Seminar Room 1\, Newton Institute
END:VEVENT
END:VCALENDAR