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Multidisciplinary approaches to understanding collective cell migration in developmental biology
File(s)
160056.full.pdf (570.57 KB)
Published version
OA Location
Author(s)
Schumacher, LJ
Kulesa, PM
McLennan, R
Baker, RE
Maini, PK
Type
Journal Article
Abstract
Mathematical models are becoming increasingly integrated with experimental efforts in the study of biological systems. Collective cell migration in developmental biology is a particularly fruitful application area for the development of theoretical models to predict the behaviour of complex multicellular systems with many interacting parts. In this context, mathematical models provide a tool to assess the consistency of experimental observations with testable mechanistic hypotheses. In this review, we showcase examples from recent years of multidisciplinary investigations of neural crest cell migration. The neural crest model system has been used to study how collective migration of cell populations is shaped by cell–cell interactions, cell–environmental interactions and heterogeneity between cells. The wide range of emergent behaviours exhibited by neural crest cells in different embryonal locations and in different organisms helps us chart out the spectrum of collective cell migration. At the same time, this diversity in migratory characteristics highlights the need to reconcile or unify the array of currently hypothesized mechanisms through the next generation of experimental data and generalized theoretical descriptions.
Date Issued
2016-06-08
Date Acceptance
2016-05-05
Citation
Open Biology, 2016, 6
URI
DOI
ISSN
2046-2441
Publisher
The Royal Society
Journal / Book Title
Open Biology
Volume
6
Copyright Statement
© 2016 The Authors.
Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
License URL
Subjects
collective cell migration
developmental biology
mathematical modelling
neural crest
Publication Status
Published
Article Number
160056