In recent years, Bioinformatics and Computational Biology have proven to be invaluable in biomedical research. The major goal of our laboratory is to develop statistically rigorous computational tools that will accelerate research in human cancer genetics and eventually translate into the clinical setting.  We have developed several programs, which contribute toward the efficient characterization of genomic sequences and promoters.

	CpG Island Finder classifies a genomic region to be CpG or non-CpG related. This program uses a sliding window of 201 bp in length and calculates the dinucleotide percentage for each window.
	P53Scanner predicts potential P53 consensus binding sites. It implements a position weight matrix built from experimentally-characterized data and comparative genomics approaches.
	FirstEF predicts the first exon and promoter regions in the human genome. The probabilistic models are designed to find potential first splice-donor sites as well as CpG-related and non-CpG-related promoter regions based on discriminant analysis.
	GDVTK, Genome Data Visualization Tool Kit, is a sound framework for developing web-based applciations to present the gene regulatory region annotations in visual form. GDVTK has been implemented in the several databases developed by our group.