Development and implementation of ontology-based systems for mammalian gene expression profiling
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The use of ontologies in the mapping of gene expression events provides an effective and comparable method to determine the expression profile of an entire genome across a large collection of experiments derived from different expression sources. In this dissertation I describe the development of the developmental human and mouse eVOC ontologies and demonstrate the ontologies by identifying genes showing a bias for developmental brain expression in human and mouse, identifying transcription factor complexes, and exploring the mouse orthologs of human cancer/testis genes.Model organisms represent an important resource for understanding the fundamental aspects of mammalian biology. Mapping of biological phenomena between model organisms is complex and if it is to be meaningful, a simplified representation can be a powerful means for comparison. The implementation of the ontologies has been illustrated here in two ways.Firstly, the ontologies have been used to illustrate methods to determine clusters of genes showing tissue-restricted expression in humans. The identification of tissue restricted genes within an organism serves as an indication of the finetuning in the regulation of gene expression in a given tissue. Secondly, due to the differences in human and mouse gene expression on a temporal and spatial level, the ontologies were used to identify mouse orthologs of human cancer/testis genes showing cancer/testis characteristics. With the use of model systems such as mouse in the development of gene-targeted drugs in the treatment of disease, it is important to establish that the expression characteristics and profiles of a drug target in the model system is representative of the characteristics of the target in the system for which it is intended.