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Computational Biology Institute
45085 University Drive
Ashburn, Virginia 20147
- Professor of Biological Sciences
- Director, Computational Biology Institute
- Principal Investigator (PI), Computational Biology Institute
In June of 2012 The George Washington University hired Professor Keith Crandall, a widely respected researcher and chair of the biology department at Brigham Young University, as director of its planned Computational Biology Institute. Dr. Crandall earned a Ph.D. in population and evolutionary biology and a master’s degree in statistics, both from Washington University in St. Louis. He completed postdoctoral work at the University of Texas on an Alfred P. Sloan and National Science Foundation fellowship.
Professor Crandall’s research work focuses on the development and testing through computer simulation of methods for the analysis of DNA sequence data. He has developed methods for estimating gene genealogies, detecting recombination, detecting selection, and measuring genetic diversity and demographic events in the history of a population. He has developed software to implement and test these methods and many others by comparison through computer simulation. Through comparison and tests of robustness to assumption violations, he hopes to gain insight into why particular methods perform well or poorly and then are in a good position to redevelop improved methodology. Professor Crandall is applying these methodologies in two very distinct areas. The first is in molecular ecology, conservation biology, and systematics research. We have applied the methods developed and tested in our lab (and many others) to examine the populations genetics, historical demography, and molecular ecology of various species of freshwater crayfish. The second focus of is in the area of the evolution of infectious diseases. Here the main has been HIV, but he is also very active in bacterial genetics, especially Neisseria gonorrhoeae. The main goal of this research is to explore the population dynamics of infectious disease, particularly relative to the evolution of drug resistance.