Address87 E Canfield Detroit MI 48201
3rd floor Mid Med building
• Statistical computing/bioinformatics
• Statistical genetics
• Methodology development for high throughput data analyses
• Design of experiments
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.
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