Presenter
Simon Gregory, PhD

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Biosketch
Simon G. Gregory, PhD, is an Assistant Professor in the Section of Medical Genetics, Department of Medicine. Dr. Gregory's role in the Duke CHG is to apply the experience gained from leading the mapping of the mouse genome and sequencing human chromosome 1 to elucidating the molecular mechanisms underlying multi-factorial diseases. His primary area of research involves the identification of the complex genetic factors that give rise to the development of cardiovascular disease and the detection of genes involved in multiple sclerosis. Dr. Gregory's group is also pioneering the application of high-resolution genomic micro arrays for the discovery of chromosomal abnormalities and identification of epigenetic factors associated with human diseases such as cancer and autism. This project aims to correlate copy number profiles and factors such as methylation, with clinical phenotypes and differential levels of gene expression. His areas of special expertise are genome mapping, positional cloning and determining the effect that sequence variation has upon the etiology of genetic disease. Dr. Gregory is also director of the CHG Molecular Genetics Core facility and the Duke Bioinformatics Workshop, a forum for researchers to gain in-depth experience of using publicly available molecular genomics databases.

Abstract
The finished sequence of the human genome represents an invaluable resource that will greatly accelerate scientific research. However, the bewildering array of genomic information, analysis tools, and ancillary databases are difficult to navigate without being properly equipped with skills necessary to make optimal use of these data. The major factors that will influence the use of this vast amount of data is the awareness of the diversity of data that is publicly available and the skills required to make full use of it. This lecture will touch on the content, i.e. utilization of evolving biological databases and the innovative tools with which they are queried, and the inherent strengths and weaknesses of the analyses they perform.