Greg Dyson

Greg Dyson

Associate Professor


Greg Dyson


87 E Canfield Detroit MI 48201

Office Address

 3rd floor Mid Med building



Research Interests

• Statistical computing/bioinformatics
• Statistical genetics
• Methodology development for high throughput data analyses
• Design of experiments

Research Description

My research focuses on developing statistical methodologies to determine whether genetic variations improve the ability to predict disease beyond what is known from traditional risk factors. As a result, a new data mining tool was developed (an augmented version of the Patient Rule-Induction Method) that has been utilized to identify sub-groups of a population of interest where genetic variations are predictive of cardiovascular disease and cancer. I collaborate with multiple principal investigators who study a wide range of cancer types to design experiments, analyze data and interpret results to address research hypotheses. I have published multiple papers on gene expression data analysis methodology from background correction and normalization to test statistic construction. My current research interests include methodology development and analysis of next-generation data.

Recent Publications

Shaik AN, Kiavash K, Stark K, Boerner JL, Ruterbusch JJ, Deirawan H, Bandyopadhyay S, Ali-Fehmi R, Dyson G, Cote ML. Inflammation markers on benign breast biopsy are associated with risk of invasive breast cancer in African American women. Breast Cancer Res Treat. 2021;185:831-9.

Mpilla GB, Uddin MH, Al-Hallak MN, Aboukameel A, Li Y, Kim SH, Beydoun R, Dyson G, Baloglu E, Senapedis WT, Landesman Y, Wagner KU, Viola NT, El-Rayes BF, Philip PA, Mohammad RM, Azmi AS. (2021) PAK4-NAMPT Dual Inhibition Sensitizes Pancreatic Neuroendocrine Tumors to Everolimus. Mol Cancer Ther 2021;20:1836-45.

Dyson, G. An Application of the Patient Rule-Induction Method to Detect Clinically Meaningful Subgroups from Failed Phase III Clinical Trials. Int J Clin Biostat Biom. 2021;7:038.

Bao B, Teslow EA, Mitrea C, Boerner JL, Dyson G, Bollig-Fischer A. Role of TET1 and 5hmC in an Obesity-Linked Pathway Driving Cancer Stem Cells in Triple-Negative Breast Cancer. Mol Cancer Res. 2020;18:1803-14.

Dyson G, Farran B, Bolton S, Craig DB, Dombkowski A, Beebe-Dimmer JL, Powell IJ, Podgorski I, Heilbrun LK, Bock CH. The extrema of circulating miR-17 are identified as biomarkers for aggressive prostate cancer. Am J Cancer Res 2018;8:2088-95. 


B.A. 1999 Canisius College History, Mathematics, Political Science
Ph.D. 2004 University of Michigan Statistics

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