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Title: Exploring the genotype-phenotype map for gene regulatory networks capable of pattern formation
Author: Cotterell, James Lloyd
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2008
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Patterning mechanisms are controlled by regulatory networks of genes of different cells interacting together to act like a cellular computer. Traditional approaches worked on a case by case basis, analyzing gene networks responsible for specific pattern formation phenomena and exploring how they function by reverse genetics. More recently systems biology approaches have been used to explore how these gene networks function, extracting features that are only apparent on a system scale. These approaches require the computational modelling of the underlying gene regulatory networks controlling the individual patterning phenomena in a spatial context. They have been successful in identifying widespread phenomena such as the robustness of network function to mutation and noise. Due to the advent of more powerful computers, we now believe systems biology can go much further. Instead of limiting ourselves to the gene networks we know are responsible for pattern formation in specific systems, we can model all possible gene networks up to a particular level of complexity (number of genes and interactions). By modelling all possible regulatory networks in a spatial context we are exploring how network structure (genotype) relates to the possible gene expression patterns (phenotype). Fundamental design and evolutionary principles can be extracted by mapping out the space of possibilities in this fashion, which is not possible by analyzing real gene networks on a case by case basis. As a by product, by using a realistic model of gene regulation, new non-intuitive patterning mechanisms can also be discovered and suggested to account for observed patterning phenomena in real biological systems.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available