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Structured models of cell migration incorporating molecular binding processes

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JMB_DomschkeTrucuGerischChaplain_PURE.pdf (903.9Kb)
Date
12/2017
Author
Domschke, Pia
Trucu, Dumitru
Gerisch, Alf
Chaplain, Mark Andrew Joseph
Keywords
Structured population modelling
Spatio-temporal model
Cell-surface receptors
Cancer invasion
QA Mathematics
QH301 Biology
RC0254 Neoplasms. Tumors. Oncology (including Cancer)
NDAS
BDC
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Abstract
The dynamic interplay between collective cell movement and the various molecules involved in the accompanying cell signalling mechanisms plays a crucial role in many biological processes including normal tissue development and pathological scenarios such as wound healing and cancer. Information about the various structures embedded within these processes allows a detailed exploration of the binding of molecular species to cell-surface receptors within the evolving cell population. In this paper we establish a general spatio-temporal-structural framework that enables the description of molecular binding to cell membranes coupled with the cell population dynamics. We first provide a general theoretical description for this approach and then illustrate it with three examples arising from cancer invasion.
Citation
Domschke , P , Trucu , D , Gerisch , A & Chaplain , M A J 2017 , ' Structured models of cell migration incorporating molecular binding processes ' , Journal of Mathematical Biology , vol. 75 , no. 6-7 , pp. 1517-1561 . https://doi.org/10.1007/s00285-017-1120-y
Publication
Journal of Mathematical Biology
Status
Peer reviewed
DOI
https://doi.org/10.1007/s00285-017-1120-y
ISSN
0303-6812
Type
Journal article
Rights
© 2017, Springer-Verlag Berlin Heidelberg. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1007/s00285-017-1120-y
Description
DT and MAJC gratefully acknowledge the support of the ERC Advanced Investigator Grant 227619, “M5CGS - From Mutations to Metastases: Multiscale Mathematical Modelling of Cancer Growth and Spread”.
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/13127

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