The torrent of data flowing from advances in genomic technology has overwhelmed current analytical capabilities.  The goal of the Program in Computational Genetics (PCG) is to use the latest approaches in computational biology, computer science, bioinformatics, and statistics to develop and apply methods to sort through the increasingly rich genomic data sets for complex genetic patterns.  The CHGR faculty is on the cutting edge of development of new methods of analysis as well as the innovative application of these methods to understanding the underlying etiology of complex diseases, with a particular focus on discovering gene x gene and gene x environment interactions.  The CHGR faculty are internationally recognized for their development of interactions detection methods.  Unique to the PCG is our integrated approach to these complex problems.  Methods development is integrated with and driven by the application to real-life analytical problems.  Experts in all areas of complex disease process including molecular biologists, statisticians, clinicians, and bioinformaticians are encouraged and essential to the success of the PCG.