Ph. D. Thesis Computational Methods for Analyzing the Architecture and Evolution of the Regulatory Genome

Diversity in forms of animal life, diversity in function of an organisms cells, and diversity in function of a single cell over its lifetime or in response to different stimuli drives a whole plethora of processes in biology. Gene control circuitry actually dictates whether or not, and when and by how much a particular gene should be expressed in a cell in order to create such diversity. Such control mechanisms are often present in the genome in the form of cis-regulatory modules: regions in the neighborhood of each gene which contain sequence motifs (particular genetic subsequences which are noisy copies of each other) where proteins (called Transcription Factors) that regulate the gene expression bind. The large amounts of genomic (and often other corresponding experimental) data involved, and the complexity of the resulting analysis lends itself well to a machine learning