Dr. Nathan Tintle of the Hope College mathematics faculty has received support from the National Institutes of Health (NIH) as he seeks to help researchers who are sifting through the staggering volume of genetic data now available to identify factors related to health and disease.
Tintle, an assistant professor of mathematics, has received a $193,500, three-year grant from the NIH's National Human Genome Research Institute for his project "Evaluating the Cost-Effectiveness of Alternative Sample Designs for Genetic Association." He and his team of Hope student researchers are examining how genetic studies look at data, and hope to determine and recommend more cost-effective approaches for working with the information and to develop free Web-based tools for those conducting such studies.
"The number of research efforts to find genetic variants that predispose to human disease via genetic association studies has grown significantly since the completion of both the Human Genome Project and the International HapMap Project. In this research we consider alternate sample design methodologies for genetic association studies, with the goal of maximizing statistical power for testing genotype-phenotype association," he said. "Maximizing statistical power will allow researchers to more quickly and efficiently identify genetic variants predisposing individuals to complex human diseases."
The award will support Tintle's work through the spring of 2011.
Tintle has been a member of the Hope faculty since 2005. In January the college named him a "Towsley Research Scholar," recognition that includes support for his ongoing research efforts.
He graduated from the State University of New York (SUNY) at Albany in 2000 with a major in mathematics, and completed Master of Science and doctoral degrees in statistics at SUNY-Stony Brook in 2003 and 2004 respectively.
While completing his graduate work he was lead statistical analyst with the department of psychiatry at SUNY-Stony Brook, which he continues to serve as a consultant. His publications include articles based on both his primary and ongoing interest in statistical genetics and his work with SUNY-Stony Brook's researchers in psychiatry.