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About MaPS

interior photo displaying students in lounge

The Department of Microbiology and Physiological Systems was founded in 2010 and emerged from two departments, one focused on microbiology, genetics, and immunology, and the other focused on physiology. Capitalizing on the strengths of each, MaPS has strong and synergistic expertise in bacterial and viral pathogenesis, immunology, signal transduction, and fundamental cellular physiology. Departmental research targets viral and bacterial pathogens affecting the nervous, respiratory, and digestive systems.

MaPS Faculty combine experimental and computational methods to understand the complex interactions between the host, the pathogen and the natural resident microbial community. Understanding how these networks change from normal physiology to disease fosters the development of computational models that simulate infection and new approaches to disease-specific diagnostics, prognostics, and therapeutics.

MaPS research shows exciting potential, when new patterns of human interaction, changes in global climate, and emergence of drug resistance have contributed to the emergence of world-wide epidemics, such as COVID-19, AIDS, influenza, and tuberculosis.

MaPS is a vibrant, growing, and highly interactive scientific community that feeds and complements UMass Chan Medical School’s growth in translational research.

MaPS Fast Facts

The Department of Microbiology and Physiological Systems (MaPS) is one of four Basic Science Departments at UMass Chan Medical School.

MaPS houses over 100 Researchers, including Lab Heads, Instructors, Postdoctoral and Doctoral Trainees, Undergraduate Students, and Summer Interns. An expert Administrative Team works tirelessly in support of the research and educational effort.

MaPS Researchers use multidisciplinary approaches that integrate genomicsproteomicshigh-resolution imaging, and computational methods to characterize networks of microbe-host interactions at the molecular, cellular, and organismal levels. Comparisons of such networks with those that define normal physiology fosters the development of computational models that simulate infection and innovative approaches to disease-specific diagnostics, prognostics, and therapeutics.

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