Greg Dyson PhD
Position Title
Professor
Population Science
Office Location
Mid-Med Lofts87 E Canfield
Detroit, MI 48201
Mailing Address
4100 John R.
Mail Code: MM03BI
Detroit, MI 48201
Office Phone
313-576-8654Office Fax
313-576-8656Education Training
Education
(2004) PhD Statistics, University of Michigan, Ann Arbor, MI
(1999) BA History, Canisius College, Buffalo, NY
(1999) BA Mathematics, Canisius College, Buffalo, NY
(1999) BA Political Science, Canisius College, Buffalo, NY
Postgraduate Training
(2002-2002) Research Internship, Bristol-Meyer Squibb, Ann Arbor, MI
(2001-2002) Research Fellowship Student, Pfizer, Ann Arbor, MI
Professional Experience
Faculty Appointments
(2024-Present) Professor, Department of Oncology, Wayne State University School of Medicine, Detroit, MI
(2017-2024) Associate Professor, Department of Oncology, Wayne State University School of Medicine, Detroit, MI
(2010-2017) Assistant Professor, Department of Oncology, Wayne State University School of Medicine, Detroit, MI
(2007-2010) Research Investigator, Human Genetics, University of Michigan, Ann Arbor, MI
Hospital or Other Professional Appointments
(2005-2007) Research Specialist, Human Genetics, University of Michigan, Ann Arbor, MI
(2004-2005) Biostatistician, Allergan: Irvine, CA
(2000-2001) Research Assistant II, School of Education, University of Michigan, Ann Arbor, MI
Major Professional Societies
American Statistical Association
Honors and Awards
(2015) WSU School of Medicine College Teaching Award
(2012) WSU School of Medicine College Teaching Award
Courses taught
CB 7600: Functional Genomics and Bioinformatics
FPH 7160: Linear Regression and ANOVA
Research Interests
My current research interests include bioinformatics, statistical genetics, methodology development for high throughput data analyses, design of experiments, design of pre-clinical studies and statistical computing.
Publications
Man MZ, Dyson G, Johnson K, Liao B (2004) Evaluating methods for classifying expression data. J Biopharm Stat 14:1065-1084. PMID: 15587980.
Dyson G, Wu CFJ (2006). MAOSA: A new procedure for detection of differential gene expression. Statist Methodol 3:42-54. PMID: NA.
Dyson G, Frikke-Schmidt R, Nordestgaard BG, Tybjærg-Hansen A, Sing CF (2007) An application of the Patient Rule-Induction Method for evaluating the contribution of the apolipoprotein E and lipoprotein lipase genes to predicting ischemic heart disease. Genet Epidemiol 31:515-527. PMID: 17436307.
Dyson G, Wu CFJ (2008) ICI: A new approach to explore between-cluster relationships with applications to gene expression data. J Biopharm Stat 18:244-255. PMID: 18327719.
Dyson G, Frikke-Schmidt R, Nordestgaard B, Tybjærg-Hansen A, Sing CF. (2009) Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease. Genet Epidemiol 33:317:24. PMID: 19025787.
Stengård JH, Dyson G, Frikke-Schmidt R, Tybjærg-Hansen A, Nordestgaard BG, Sing CF (2010). Context dependent associations between variation in risk of IHD and variation in the 5′ promoter region of the apolipoprotein E gene in Danish females, Circ Cardiovasc Genet. 3:22-30. PMID: 20160192.
Chatterjee M, Dyson G, Levin NK, Shah JP, Morris R, Munkarah A, Tainsky MA (2012) Tumor Autoantibodies as Biomarkers for Predicting Ovarian Cancer Recurrence, Cancer Biomarkers 11:59-73. PMID: 23011153.
Powell IJ, Dyson G, Land S, Ruterbusch J, Bock CH, Lenk S, Herawi M, Everson R, Giroux CN, Schwartz AG, Bollig-Fischer A. (2013) Genes associated with prostate cancer are differentially expressed in African American and European American men, Cancer Epidemiol Biomarkers Prev. 22:891-7, PMID: 23515145.
Swett, RJ, Elias A, Miller JA, Dyson G, Cisneros GA (2013). Hypothesis driven single nucleotide polymorphism search (HyDn-SNP-S). DNA Repair 12: 733-740, PMID: 23830898.
Dyson G, Sing CF. (2014). Efficient identification of context dependent subgroups of risk from genome wide association studies. Stat Appl Genet Mol, doi:10.1515/sagmb-2013-0062 [Epub ahead of print] PMID: 24570412.