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Title: An integrative modelling framework for multicellular systems
Authors: Naylor, Jonathan Robert Denby
Issue Date: 2019
Publisher: Newcastle University
Abstract: Multicellular systems exhibit complex population scale behaviour that emerge from the interactions between constituent cells. Integrative modelling (IM) techniques are a valuable tool for studying these systems capturing processes that occur at many temporal and spatial scales. The application of IM to multicellular systems is challenging as it is knowledge and resource intensive, additionally there do not exist effective frameworks or tools, inhibiting its wider application in Systems and Synthetic biology. This thesis presents Simbiotics, a novel IM framework for the modelling of mixed species bacterial consortia. Simbiotics is a spatially explicit multi-scale modelling platform for the design, simulation and analysis of bacterial populations. A library of modules simulating features such as cell geometries, physical force dynamics, genetic circuits, metabolic pathways, chemical diffusion and cell interactions is implemented, that the modeller may compose into their own custom models. Common modelling methods such as Boolean networks, differential equations, Gillespie models and SBML are implemented. With the platform in-silico experiments can be conducted with programmed experiment interactions, data collection and analysis. The framework is extendable and modular, allowing for the library to be updated as knowledge progresses. A novel file format for the reuse and communication of multicellular models and simulation methods is also implemented. Additionally an intuitive graphical user interface, Easybiotics, has been developed allowing for multicellular modelling with minimal programming experience. Four novel case studies are pursued with Simbiotics studying the emergent behaviours of multicellular systems. The effect of physical cell interactions are characterised in the first two studies. Investigation into how chemical signalling and intracellular dynamics influence population dynamics and patterns are studied in the final two case studies. These studies demonstrate how Simbotics can be integrated into a Systems/ Synthetic biology workflow, facilitating the studying of natural systems and as a CAD tool for developing novel synthetic systems.
Description: Ph. D. Thesis.
Appears in Collections:School of Computing Science

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