e-space
Manchester Metropolitan University's Research Repository

    Computational modelling of embryogenesis driven by empirical evidence from 4D microscopy images

    Dokmegang, Joel (2020) Computational modelling of embryogenesis driven by empirical evidence from 4D microscopy images. Doctoral thesis (PhD), Manchester Metropolitan University.

    [img]
    Preview

    Available under License Creative Commons Attribution Non-commercial No Derivatives.

    Download (15MB) | Preview

    Abstract

    The development of multicellular organisms remains one of the most enduring puzzles of science. While wet lab methods have proven effective in unravelling multiple mechanisms, much is yet to be discovered. Computer simulations are increasingly used in this context and present over wet lab experiments the advantages of simplicity, reduced risk and total control over experimental conditions and parameters. Hence the need for more computational models and studies establishing their usefulness for biologists. In this work, we present a novel agent-based computational model of cell and tissue mechanics (MG#) of the family of Deformable Cell Models, able to simulate various phenomena in morphogenesis. Furthermore, we show that MG# can be extended to couple mechanical and chemical variables describing the dynamics of a cell within a unified framework. Using MG#, we reproduce key morphological events of mouse implantation and, for the first time, provide theoretical evidence that trophectoderm morphogenesis can regulate epiblast shape upon implantation. Moreover, enriching centre-based models with a polarity term, we show that directed cell behaviours are a sufficient drive for zebrafish fin development. Together, the results presented in this thesis offer key insights into morphogenesis, highlight the usefulness of agent-based modelling methods in the study of embryogenesis, and propose new mathematical models, and computational tools purposed for the investigation of early development.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    100Downloads
    6 month trend
    160Hits

    Additional statistics for this dataset are available via IRStats2.

    Repository staff only

    Edit record Edit record