Rate My Professor Gregory Dyson

Gregory Dyson, PhD, is a Professor in the Department of Oncology at Wayne State University School of Medicine, with affiliations to the Karmanos Cancer Institute and the Cancer Biology Program. His academic background includes a PhD in Statistics from the University of Michigan in 2004, and BA degrees in History, Mathematics, and Political Science from Canisius College in 1999. Dyson's research specializations encompass bioinformatics, statistical genetics, methodology development for high-throughput data analyses, design of experiments, design of pre-clinical studies, and statistical computing. He focuses on statistical methodologies to evaluate whether genetic variations improve disease prediction beyond traditional risk factors, including development of an augmented Patient Rule-Induction Method data mining tool to identify context-dependent subgroups predictive of cardiovascular disease and cancer outcomes. His work supports collaborations across various cancer studies, involving experiment design, data analysis, and interpretation, with applications to gene expression data analysis including background correction, normalization, and test statistic construction, as well as next-generation sequencing data.

Dyson's career history at Wayne State University includes progression from Assistant Professor (2010-2017) to Associate Professor (2017-2024) and Professor (2024-present) in the Department of Oncology. Previous appointments feature Research Investigator in Human Genetics at the University of Michigan (2007-2010), Research Specialist there (2005-2007), Biostatistician at Allergan (2004-2005), and Research Assistant II at the University of Michigan School of Education (2000-2001). Postgraduate training comprises a Research Internship at Bristol-Myers Squibb (2002) and Research Fellowship at Pfizer (2001-2002). He has earned College Teaching Awards from the Wayne State University School of Medicine in 2012, 2015, and 2025. Key publications include 'Efficient identification of context dependent subgroups of risk from genome wide association studies' (2014, Stat Appl Genet Mol Biol), 'Genes associated with prostate cancer are differentially expressed in African American and European American men' (2013, Cancer Epidemiol Biomarkers Prev), 'The extrema of circulating miR-17 are identified as biomarkers for aggressive prostate cancer' (2018, Am J Cancer Res), 'Role of TET1 and 5hmC in an Obesity-Linked Pathway Driving Cancer Stem Cells in Triple-Negative Breast Cancer' (2020, Mol Cancer Res), and 'PAK4-NAMPT Dual Inhibition Sensitizes Pancreatic Neuroendocrine Tumors to Everolimus' (2021, Mol Cancer Ther). Dyson teaches CB 7600 Functional Genomics and Bioinformatics and FPH 7160 Linear Regression and ANOVA, and holds membership in the American Statistical Association.