Reuben Thomas

Inference of Regulatory Interactions in Genetic Systems: Optimization-based Techniques Using Microarray Data Reuben Thomas

The main focus of this thesis is the development of techniques to aid in the process of inferring how genes interact with each other in a living organism. Knowledge of these interactions have implications in gaining an understanding of how cellular processes work, how organisms survive and evolve under different environmental conditions. The techniques are based on an S-system type differential equation model for the process of gene regulation. They are designed to handle data arising from experimental setups like DNA microarrays. Methods to handle data collected under both steady state and time-varying manner are developed. They were validated using both simulated data and also data from real organisms. The data used were steady state data from the set of genes involved in the SOS response of E. Coli and time-varying data from a subset of genes involved in the formation of the endospore in the Bacillus anthracis. The techniques proposed have advantages over the current methods used in that they not only capture the inherent non-linearity of the process but also account for the regulatory behavior of proteins and handle data directly from DNA microarray experiments.