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Modeling the extracellular matrix in cell migration and morphogenesis: a guide for the curious biologist.
Crossley, Rebecca M; Johnson, Samuel; Tsingos, Erika; Bell, Zoe; Berardi, Massimiliano; Botticelli, Margherita; Braat, Quirine J S; Metzcar, John; Ruscone, Marco; Yin, Yuan; Shuttleworth, Robyn.
Afiliación
  • Crossley RM; Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.
  • Johnson S; Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.
  • Tsingos E; Computational Developmental Biology Group, Institute of Biodynamics and Biocomplexity, Utrecht University, Utrecht, Netherlands.
  • Bell Z; Northern Institute for Cancer Research, Newcastle University, Newcastle upon Tyne, United Kingdom.
  • Berardi M; LaserLab, Department of Physics and Astronomy, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
  • Botticelli M; Optics11 life, Amsterdam, Netherlands.
  • Braat QJS; Watson School of Mathematics, University of Birmingham, Birmingham, United Kingdom.
  • Metzcar J; Department of Applied Physics and Science Education, Eindhoven University of Technology, Eindhoven, Netherlands.
  • Ruscone M; Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, United States.
  • Yin Y; Department of Informatics, Indiana University, Bloomington, IN, United States.
  • Shuttleworth R; Institut Curie, Université PSL, Paris, France.
Front Cell Dev Biol ; 12: 1354132, 2024.
Article en En | MEDLINE | ID: mdl-38495620
ABSTRACT
The extracellular matrix (ECM) is a highly complex structure through which biochemical and mechanical signals are transmitted. In processes of cell migration, the ECM also acts as a scaffold, providing structural support to cells as well as points of potential attachment. Although the ECM is a well-studied structure, its role in many biological processes remains difficult to investigate comprehensively due to its complexity and structural variation within an organism. In tandem with experiments, mathematical models are helpful in refining and testing hypotheses, generating predictions, and exploring conditions outside the scope of experiments. Such models can be combined and calibrated with in vivo and in vitro data to identify critical cell-ECM interactions that drive developmental and homeostatic processes, or the progression of diseases. In this review, we focus on mathematical and computational models of the ECM in processes such as cell migration including cancer metastasis, and in tissue structure and morphogenesis. By highlighting the predictive power of these models, we aim to help bridge the gap between experimental and computational approaches to studying the ECM and to provide guidance on selecting an appropriate model framework to complement corresponding experimental studies.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Cell Dev Biol Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Cell Dev Biol Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido
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