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Bioinformatics, Biological Sciences, Climate Research, Complex Systems, Electronic Medical Record Data, Epidemiology, Genetics, Genomics, Healthcare Management and Outcomes, Human Subjects Trials and Intervention Studies, Learning Health Systems, Medical Informatics, Population Sciences, Precision Health, Public Health
Algorithms, Bayesian Methods, Causal Inference, Classification, Computational Tools for Data Science, Data Collection Design, Data Management, Data Mining, Data Quality, High-Dimensional Data Analysis, Longitudinal Data Analysis, Missing Data and Imputation, Network Analysis, Statistical Inference, Statistical Modeling, Statistics, Time Series Analysis

Samuel K Handelman

Research Assistant Professor

Internal Medicine, Gastroenterology, Michigan Medicine

Samuel K Handelman, Ph.D., is Research Assistant Professor in the department of Internal Medicine, Gastroenterology, of Michigan Medicine at the University of Michigan, Ann Arbor. Prof. Handelman is focused on multi-omics approaches to drive precision/personalized-therapy and to predict population-level differences in the effectiveness of interventions. He tends to favor regression-style and hierarchical-clustering approaches, partially because he has a background in both statistics and in cladistics. His scientific monomania is for compensatory mechanisms and trade-offs in evolution, but he has a principled reason to focus on translational medicine: real understanding of these mechanisms goes all the way into the clinic. Anything less that clinical translation indicates that we don’t understand what drove the genetics of human populations.