File:Thesis-danielle.pdf

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Thesis-danielle.pdf(file size: 3.21 MB, MIME type: application/pdf)

Cellular processes are controlled by networks of interacting genes and molecules. In the cell the product of the expression of one gene can a�ect the expression of another, creating a network structure in which genes regulate each other through their products. The emergent properties of these and other networks determine the behavior of the cell. Much is unknown about these complex gene regulatory networks. Understanding how these networks work and what they look like provides us with a greater insight into the inner workings of the cell. We have focused our e�orts on improving the Hematopoietic gene regulatory network. This particular network is responsible for the di�erentiation of stem cells to a diverse range of blood cells. At each stage of this di�erentiation the cell stabilizes to a distinct steady state. The emergence of these steady states is an intrinsic property of the network itself and can be examined by creating a state space graph. The structure of the state space reveals information about the steady states the gene regulatory network contains. With this information we have devised a method in order to improve a gene regulatory network using a priori knowledge of the network topology and steady state analysis. A multi- objective Evolutionary Algorithm iteratively alters the gene regulatory network and uses the steady state information and topological a priori knowledge as a quality measure of the network. The proposed method is an e�cient way to pinpoint where the current consensus network might be improved. With this we will attempt to improve the indicative quality of the gene regulatory net- work. It can result in new ideas for research and could help solve complicated topology issues. As a result of our research and the issues we encountered we propose that a new modeling method to represent the gene regulatory network could help solve some of these issues and we expect this representation to attain better results. This because it is more similar to the manner in which the interactions occur in the cell and because it is designed speci�cally to be edited by an Evolutionary Algorithm.

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current09:00, 12 March 2013 (3.21 MB)Ehaasdi (talk | contribs)Cellular processes are controlled by networks of interacting genes and molecules. In the cell the product of the expression of one gene can a�ect the expression of another, creating a network structure in which genes regulate each other through their pr
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