GeneHuggers: In silico detection of transcriptional regulatory motifs using genomic sequence and DNA microarray data

Bioinformatics has become an integral component to post-genomic biological research. Understanding cancer biology requires the ability to both utilize high-throughput molecular methods such as gene expression profiling and the ability to interpret the large amounts of data associated with these methods. In order to use expression profiling data to understand transcriptional regulatory mechanisms, computational methods that integrate information from multiple sequence databases and methods that integrate results obtained from various sequence analysis algorithms are required. This thesis contains work related to obtaining and characterizing targets relevant to cellular transformation. The biological subject depended on the utilization of DNA microarrays for target identification. Work with such data lead to the desire to use the human genome sequence in conjunction with array results to predict transcriptional regulatory mechanisms responsible for the observed changes in gene expression. As a result, novel bioinformatics software called GeneHuggers was developed. Genomic analyses were performed with GeneHuggers and a combination of other freely available software to attempt to establish correlations between non-coding transcriptional regulatory sequence motifs and gene expression.