A systems biology approach to multi-scale modelling and analysis of planar cell polarity in drosophila melanogaster wing
Year: 2013
Type: dissertation
Abstract: Systems biology aims to describe and understand biology at a global scale where biological systems function as a result of complex mechanisms that happen at several scales.Modelling and simulation are computational tools that are invaluable for description, understanding and prediction these mechanisms in a quantitative and integrative way.Thus multi-scale methods that couple the design, simulation and analysis of models spanning several spatial and temporal scales is becoming a new emerging focus of systems biology.This thesis uses an exemplar -Planar cell polarity (PCP) signalling -to illustrate a generic approach to model biological systems at different spatial scales, using the new concept of Hierarchically Coloured Petri Nets (HCPN).PCP signalling refers to the coordinated polarisation of cells within the plane of various epithelial tissues to generate sub-cellular asymmetry along an axis orthogonal to their apical-basal axes.This polarisation is required for many developmental events in both vertebrates and non-vertebrates.Defects in PCP in vertebrates are responsible for developmental abnormalities in multiple tissues including the neural tube, the kidney and the inner ear.In Drosophila wing, PCP is seen in the parallel orientation of hairs that protrude from each of the approximately 30,000 epithelial cells to robustly point toward the wing tip.This work applies HCPN to model a tissue comprising multiple cells hexagonally packed in a honeycomb formation in order to describe the phenomenon of Planar Cell Polarity (PCP) in Drosophila wing.HCPN facilitate the construction of mathematically tractable, compact and parameterised large-scale models.Different levels of abstraction that can be used in order to simplify such a complex system are first illustrated.The PCP system is first represented at an abstract level without modelling details of the cell.Each xiii
Author: Qian Gao
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W39729975