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Modeling and evolutionary analysis of gene regulatory networks

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dc.contributor Graduate Program in Biomedical Engineering.
dc.contributor.advisor Güveniş, Albert.
dc.contributor.advisor Özen, Cem.
dc.contributor.author Uğurcuklu, Seher.
dc.date.accessioned 2023-03-16T13:12:40Z
dc.date.available 2023-03-16T13:12:40Z
dc.date.issued 2014.
dc.identifier.other BM 2014 U48
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/18847
dc.description.abstract In Systems Biology and more recently emerging eld of Synthetic Biology, mathematical modeling has become an indispensable component of research. As complementary to the experimental studies, computer simulations are used to accelerate the hypothesis generation-validation cycle of research in biological systems. This thesis is mainly concerned with modeling and inference of gene regulatory dynamics on the basis of gene expression patterns. At rst, we make a statistical analysis over randomly generated genetic networks, based on their oscillatory dynamics. Then, in our model problem, we aim to design a family of genetic networks that exhibit stable periodic oscillations with a prescribed period. Later, we investigate the temporal behaviour of a system utilizing a computer simulation. We design such circuits on the basis of in silico evolution of the corresponding network model. The approach starts with a randomized gene network. Then, structural rewiring mutations are applied to the networks. In this process, evolving networks are selected depending on their closer approach to the targeted dynamics, after a mutation. By using this method, networks with required oscillation periods are constructed by changing the architecture of regulatory connections between the genes. In addition, we choose a small genetic network that exhibits chaotic dynamics, and look at the change of its dynamics against a system parameter. Such an approach is useful in deriving the characteristics of these systems under speci c variations.|Keywords : Dynamical Systems, Gene Regulatory Networks, Evolutionary Algorithm, Mathematical Modeling, Inference, Optimization.
dc.format.extent 30 cm.
dc.publisher Thesis (M.S.)-Bogazici University. Institute of Biomedical Engineering, 2014.
dc.subject.lcsh Systems biology -- Mathematical models.
dc.subject.lcsh Systems biology -- Mathematical models.
dc.subject.lcsh Synthetic biology.
dc.title Modeling and evolutionary analysis of gene regulatory networks
dc.format.pages x, 58 leaves ;


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