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School of Medicine establishes new Center for Statistical Genetics and Genomics

The School of Medicine has launched the new Center for Statistical Genetics and Genomics. The center, led by Andrew Allen, PhD, professor of Biostatistics and Bioinformatics, will bring together quantitatively-oriented scientists from various disciplines on the Duke campus to address the computational and statistical challenges associated with efforts to use genomics to improve patient care.

“This center, under Dr. Allen’s leadership, will help establish Duke as a leading center of genomic-focused statistical and computational methods development,” said Nancy C. Andrews, MD, PhD, Dean, Duke University School of Medicine.  Dr. Liz DeLong, Chair of the Department of Biostatistics and Bioinformatics added, “The creation of this Center is a timely expansion of the emphasis on genetics and genomics at Duke.  In partnership with the Duke Center for Genomic and Computational Biology and the Duke Center for Personalized and Precision Medicine, this Center completes a comprehensive and powerful initiative toward advancing science in this area.  There is no better person to lead the Center than Andrew, who has the methodological stature and the collaborative personality to bring researchers together to attack the many statistical and computational challenges that are currently preventing us from realizing the promise genetics and genomics holds for medical care.”

Under Dr. Allen’s leadership, the center will bring together quantitative talent in working groups focusing on key problems in genomic medicine. These working groups will include scientists from various disciplines (Math, Biostatistics, Statistics, Engineering, etc.).   The presence of these diverse skill sets and perspectives will create a rich educational and research environment. The center will involve trainees from various educational programs in a common laboratory environment where they will work together in teams to solve problems.

“Sophisticated computational and statistical methods are required to advance our knowledge of disease biology as well as to identify important, treatment-relevant features of individual patient genomes. It is essential that, as an institution, Duke not only be a sophisticated user of these techniques and create an infrastructure for their principled use, but that Duke becomes a leader in this field and push the development of computational and statistical approaches that respond to existing or emerging challenges,” said Dr. Allen.

“This mixing of various perspectives and backgrounds will help break down traditional barriers between disciplines and will form a potent model for the development of future quantitative genomic scientists,” said Dr. Allen.