Honors Courses: Lafayette

Associate Professor, Computational and Systems Biology, University of Pittsburgh School of Medicine
Marcus Noyes is an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. His laboratory focuses on the development of gene therapies to address rare as well as complex disease. Primarily a protein engineer, Dr Noyes studies how proteins recognize and interact with DNA and how those interactions can be understood well enough to engineer new biological functions. His research combines synthetic biology, large-scale experimentation, computational modeling, and artificial intelligence to design proteins that can control gene activity, with potential applications ranging from understanding human genetic variation to developing new therapeutic approaches.
Noyes took a somewhat unconventional path into science. After spending several years pursuing a career as a musician, he attended Hamline University in St. Paul, Minnesota, where he studied both Biology and Psychology. He went on to earn his Ph.D. in Biochemistry from the University of Massachusetts Medical School, where his work on protein-DNA interactions and genome engineering received both the university’s Outstanding Thesis Research Award and the Harold M. Weintraub Graduate Student Award. Rather than following the traditional postdoctoral route, he was appointed an independent Lewis-Sigler Fellow at Princeton University, where he ran his own laboratory, taught, and mentored students before joining the faculty at NYU School of Medicine and, later, the University of Pittsburgh.
A recurring theme in Noyes’s research and teaching is how we move from observation to explanation. What makes a question scientifically testable? How do we design an experiment that distinguishes among competing explanations? And when we say that one result is “better” than another, what exactly are we measuring? These questions are as relevant to understanding genes and proteins as they are to understanding why a cookie is chewy, why one person loves a particular food and another does not, or why cuisines developed differently around the world.