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Quantitative analysis of cellular networks: cell cycle entry

dc.contributor.advisor You, Lingchong Lee, Tae J. 2010-05-10T19:55:53Z 2010-05-10T19:55:53Z 2010
dc.description.abstract <p>Cellular dynamics arise from intricate interactions among diverse components, such as metabolites, RNAs, and proteins. An in-depth understanding of these interactions requires an integrated approach to the investigation of biological systems. This task can benefit from a combination of mathematical modeling and experimental validations, which is becoming increasingly indispensable for basic and applied biological research. </p> <p>Utilizing a combination of modeling and experimentation, we investigate mammalian cell cycle entry. We begin our investigation by making predictions with a mathematical model, which is constructed based on the current knowledge of biology. To test these predictions, we develop experimental platforms for validations, which in turn can be used to further refine the model. Such iteration of model predictions and experimental validations has allowed us to gain an in-depth understanding of the cell cycle entry dynamics. </p> <p>In this dissertation, we have focused on the Myc-Rb-E2F signaling pathway and its associated pathways, dysregulation of which is associated with virtually all cancers. Our analyses of these signaling pathways provide insights into three questions in biology: 1) regulation of the restriction point (R-point) in cell cycle entry, 2) regulation of the temporal dynamics in cell cycle entry, and 3) post-translational regulation of Myc by its upstream signaling pathways. The well-studied pathways can serve as a foundation for perturbations and tight control of cell cycle entry dynamics, which may be useful in developing cancer therapeutics. </p> <p>We conclude by demonstrating how a combination of mathematical modeling and experimental validations provide mechanistic insights into the regulatory networks in cell cycle entry.</p>
dc.format.extent 5766628 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject Engineering, Biomedical
dc.subject Biophysics, General
dc.subject Biology, Cell
dc.subject Bistable switch
dc.subject Cell Cycle
dc.subject Cell-to-cell variability
dc.subject Mathematical Modeling
dc.subject Quantitative analysis
dc.subject Systems biology
dc.title Quantitative analysis of cellular networks: cell cycle entry
dc.type Dissertation
dc.department Biomedical Engineering

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