Biographical Information

Brian Athey

Dr. Brian Athey received his Ph.D. in Cellular and Molecular Biology (Biophysics concentration) from the University of Michigan in 1990, with a research focus in macromolecular structural biology. Dr. Athey is currently an Associate Professor of Biomedical Informatics in the University of Michigan Medical School Department of Psychiatry and also an Associate Professor of Bioinformatics and Computational Biology in the UM Bioinformatics. In addition, he is Director of the Michigan Center for Biological Information (MCBI), the Bioinformatics Computing and Digital Library Hub of the Michigan Life Science Corridor (MLSC) Infrastructure Initiative. Brian was recently named Associate Director of the University of Michigan Center for Computational Medicine and Biology where his is responsible for the computing and data infrastructure build out for the Center and the Medical School.

During his Ph.D. thesis research in the 1980s, Brian proposed the double helical crossed-linker model for the structure of chromatin, at that time controversial, but now thought to be the correct model for this critical macromolecular complex, and featured in many textbooks. Brian is best known for his work with the National Library of Medicine (NLM) Visible Human Project where he has been a leader in establishing a nationwide Internet2 end-to-end test bed demonstration project with NIH/NLM sponsorship in collaboration with Pittsburgh Supercomputing Center, Stanford University, and the Uniformed Services University of the Health Sciences (USUHS). This lead to the establishment of the very successful DARPA Virtual Soldier Project, a nationwide consortium that he runs that builds from the visible human project to extend from basic human anatomy to physiological modeling, functional simulation and prediction after a traumatic injury. Brian is the Principal Investigator of the recently established (Fall, 2005) National Center for Integrative Biomedical Informatics whose mission is to facilitate scientific exploration of complex disease processes on a much larger scale than is currently feasible by developing interactively integrated analytical and modeling technologies to acquire or create context-appropriate molecular biology information from emerging experimental data, international genomic databases and the published literature.