Date of Award




Document Type


Degree Name

Doctor of Philosophy (PhD)


Department of Biomedical Sciences

Content Description

1 online resource (xiii, 285 pages) : illustrations (some color)

Dissertation/Thesis Chair

Scott A Tenenbaum

Committee Members

Julio A Aguirre-Ghiso, Thomas J Begley, Randall H Morse, David P Tuck


genomics, high-throughput, hypothesis-generation, locus-based, microarray, Genomics

Subject Categories

Bioinformatics | Computer Sciences | Molecular Biology


Genomics data is growing at a exponential rate. The ability to integrate new results with existing knowledge about genomic biology is rapidly becoming the limiting factor as there no universal language with which to describe genomic functional elements. To integrate and compare new and existing genomic data, we define our basic functional unit of a genome to be a locus -- a set of positional coordinates along any genome with an arbitrary amount of functional annotations attached. The locus concept enables addressing genomic elements and annotations at any level of granularity from entire swaths of chromosomes to single base-positions. We define a locus-based framework to compare a given set of genomic elements to any of existing genomic annotations. We use this to build a tool to find genomic annotations significantly and frequently overlaping with a set. We also use this to build a tool to infer functional interactions from locus intersections and show how the inference of regulatory interactions from genomics data and the analysis of the topological properties of genomic networks can provide useful biological insights.