Browsing by Subject "Cell Cycle"
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Item Comparative Performance Analysis of the Algorithms for Detecting Periodically Expressed Genes(2012-10-19) Agyepong, KwadwoThus far, a plethora of analysis on genome-wide gene expression microarray experiments on the cell cycle have been reported. Time series data from these experiments include gene expression profiles that might be periodically expressed. However, the numbers and actual genes that are periodically expressed have not been reported with consistency, analysis on similar experiments reports disparate numbers of genes that are periodically expressed with scant overlap. This work ultimately compares the performance of five spectral estimation schemes in their ability to recover periodically expressed genes profiles. Lomb-Scargle (LS), Capon, Missing-Data Amplitude and Phase Estimation (MAPES), Real Value Iterative Adaptive Approach (RIAA) and Lomb-Scargle Periodogram Regression (LSPR) are rigorously studied and pitted against each other in various simulated testing conditions. Results obtained using synthetic and microarray data reveals that RIAA is an efficient and robust method for the detection of periodically expressed genes in short time series data that might be characterized with noisy and irregularly sampled data points.Item Pathways, Networks and Therapy: A Boolean Approach to Systems Biology(2012-07-16) Layek, RitwikThe area of systems biology evolved in an attempt to introduce mathematical systems theory principles in biology. Although we believe that all biological processes are essentially chemical reactions, describing those using precise mathematical rules is not easy, primarily due to the complexity and enormity of biological systems. Here we introduce a formal approach for modeling biological dynamical relationships and diseases such as cancer. The immediate motivation behind this research is the urgency to find a practicable cure of cancer, the emperor of all maladies. Unlike other deadly endemic diseases such as plague, dengue and AIDS, cancer is characteristically heterogenic and hence requires a closer look into the genesis of the disease. The actual cause of cancer lies within our physiology. The process of cell division holds the clue to unravel the mysteries surrounding this disease. In normal scenario, all control mechanisms work in tandem and cell divides only when the division is required, for instance, to heal a wound platelet derived growth factor triggers cell division. The control mechanism is tightly regulated by several biochemical interactions commonly known as signal transduction pathways. However, from mathematical point of view, these pathways are marginal in nature and unable to cope with the multi-variability of a heterogenic disease like cancer. The present research is possibly one first attempt towards unraveling the mysteries surrounding the dynamics of a proliferating cell. A novel yet simple methodology is developed to bring all the marginal knowledge of the signaling pathways together to form the simplest mathematical abstract known as the Boolean Network. The malfunctioning in the cell by genetic mutations is formally modeled as stuck-at faults in the underlying Network. Finally a mathematical methodology is discovered to optimally find out the possible best combination drug therapy which can drive the cell from an undesirable condition of proliferation to a desirable condition of quiescence or apoptosis. Although, the complete biological validation was beyond the scope of the current research, the process of in-vitro validation has been already initiated by our collaborators. Once validated, this research will lead to a bright future in the field on personalized cancer therapy.Item The RASSF1A Tumor Suppressor Regulates a Cascade of Oncogenic Signals That Are Restrained by G1(2012-07-17) Ram, Rosalyn Ruanga; White, Michael A.The RASSF1A tumor suppressor is one of the most commonly inactivated genes in cancer. To understand why epigenetic silencing of RASSF1A promotes tumorigenesis, I employed a loss of function approach to elucidate the role of RASSF1A in cancer. RASSF1A is reported to regulate apoptosis, cell cycle progression, and microtubule dynamics. Disruption of these processes by RASSF1A loss may disrupt cellular integrity and promote oncogenesis. I found that RASSF1A depletion elevated oncogenic signaling pathways; however, RASSF1A depletion also induced cell cycle arrest. RASSF1A is a critical regulator in maintaining the balance between pro-growth and anti-growth signals. RASSF1A suppresses proliferative signaling pathways such as the MAPK pathway, promotes apoptosis through MST2, but paradoxically, promotes G1/S progression through modulation of the ubiquitin ligase SCF-BTrCP. Thus, RASSF1A represents a critical line of defense against tumorigenesis as its loss triggers cell arrest; however, loss of RASSF1A also promotes proliferative signaling events, and additional malfunctions in cell cycle regulation will likely drive tumorigenesis. [Keywords: RassflA, mir21, SKp2, REST, SCFBTRCP]