PhD Applied Mathematics, University of Arizona
Doctoral work, Mathematical & LIfe Sciences, Hiroshima University
Doctoral Work, Mathematical Institute, University of Oxford
MS, Applied Mathematics, University of Arizona
BS, Mathematics, University of Puget Sound
Dr. Peter Tonellato’s current research focus is three fold: (1) Development and applications of methods of biomedical informatics, mathematical modeling and simulations to characterize and predict the use of genetics in medical practice and in particular pathology. (2) Extension of those methods and analysis to predict the implication, outcome and efficacy of the use of genetics when applied to large mixed populations such as large urban centers in the United States or large but more homogeneous populations such as those found in Asia or the Middle East or in certain zip-code bound regions in the United States. And (3) Apply and test the use of high-throughput genetic technologies such as microarrays and next generation sequencers in the discovery and applications of genetics to complex diseases and environmental-gene development pathways.
Dr. Tonellato holds equal appointments in the Zilber School of Public Health at UW-Milwaukee and the Center for Biomedical Informatics (CBMI) at Harvard Medical School. The Laboratory for Personalized Medicine and the Laboratory for Public Health Informatics and Genomics, for which he is PI, develop strategies, methods, bioinformatic tools, simulations and analyses to study, test and predict the accuracy and clinical efficacy of genetic discoveries and accelerate their translation to practical clinical use (Harvard Medical School) and their application to public health and health disparities (Zilber School of Public Health). In 2009, he was awarded an NIH EUREKA grant to create ‘clinical avatars’ used to simulate realistic patient populations, provide a collection of electronic medical records used to test the efficacy of genetic data, to quantify the accuracy of predictive algorithms and to conduct clinical trial simulations using sophisticated translational software systems such as i2b2. The lab was one of the first to establish all computational systems and services ‘on the cloud’ implemented on Amazon’s AWS environment.