How individual neurons in a nervous system give rise to complex function, behavior and consciousness in higher animals has been studied for over a century, yet scientist have only begun to understand how brains work at the molecular level. This level of study is made possible through technological advances, especially transgenic analysis of the cells that make up nervous systems. To date, no other system has been used as extensively as the nematode Caenorhabditis elegans in this pursuit. With just 302 neurons in the adult hermaphrodite, extensive neuronal maps at the anatomical, functional, and molecular level have been built over the past 30 years. One way to understand how nervous systems develop and differentiate into diverse cell types such as sensory or motor neurons that make higher level behaviors possible, is to unravel the underlying gene regulatory programs that control development. Throughout my PhD I investigated neuron type identity regulators to understand how nervous system diversity is generated and maintained using several bioinformatic approaches. First, I developed a software program and community resource tool, TargetOrtho, useful for identifying novel regulatory targets of transcription factors such as the cell type selector proteins termed terminal selectors evidenced to control terminal cell identity of 74 of the 118 neuron types in C. elegans. Analysis of terminal selector candidate target genes led to the further discovery that predicted target genes with cis-regulatory binding sites are enriched for neuron type specific genes suggesting an overarching theme of direct regulation by terminal selectors to specify cell type. Using this knowledge, I make predictions for novel regulators of neuronal identity to further elucidate how the C. elegans nervous system diversifies into 118 neuron types.

In this work, we propose a framework to develop testable hypotheses for the effects of changes in the experimental conditions on the dynamics of a biological system using mathematical models. We discuss the uncertainties present in this process and show how information from different experiment regimes can be used to identify a region in the parameter space over which subsequent mathematical analysis can be conducted. To determine the significance of variation in the parameters due to varying experimental conditions, we propose using sensitivity analysis. Using our framework, we hypothesize that the experimentally observed decrease in the survivability of bacterial populations of Xylella fastidiosa (causal agent of Pierce’s Disease) upon addition of zinc, might be because of starvation of the bacteria in the biofilm due to an inhibition of the diffusion of the nutrients through the extracellular matrix of the biofilm. We also show how sensitivity is related to uncertainty and identifiability; and how it can be used to drive analysis of dynamical systems, illustrating it by analyzing a model which simulates bursting oscillations in pancreatic β-cells. For sensitivity analysis, we use Sobol’ indices for which we provide algorithmic improvements towards computational efficiency. We also provide insights into the interpretation of Sobol’ indices, and consequently, define a notion of the importance of parameters in the context of inherently flexible biological systems. / A Dissertation submitted to the Department of Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester 2019. / April 16, 2019. / Bacterial growth, Dynamical systems, Mathematical modeling, Sensitivity analysis, Sobol Indices, Xylella fastidiosa / Includes bibliographical references. / Nick Cogan, Professor Co-Directing Thesis; M.Y. Hussaini, Professor Co-Directing Thesis; Eric Chicken, University Representative; Harsh Jain, Committee Member; Richard Bertram, Committee Member; Washington Mio, Committee Member.

Thesis (Ph. D.)--Virginia Commonwealth University, 2006. / Prepared for: Dept. of Biostatistics. Bibliography: leaves 189-198. Also available online via the Internet.

Thesis (Ph. D.)--University of Hong Kong, 2005. / Title proper from title frame. Also available in printed format.

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 91-97).

Not available / text

published_or_final_version / Statistics / Master / Master of Philosophy

published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

No description available.

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