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Dr. Dancik is interested in various aspects of bioinformatics and computational biology. His research involves applying statistical, mathematical and computational models to answer biological questions and to gain insight into biological systems. His current work focuses on the identification of genomic biomarkers in cancer and methods for mining the biomedical literature. Dr. Dancik earned an M.S. in Statistics, and a Ph.D. in Bioinformatics and Computational Biology from Iowa State University.
Dr. Dancik is the coordinator of the Bioinformatics minor at Eastern
Dancik, G.M. and Theodorescu, D.T. (2018). “Chapter 35: Personalized Medicine.” In J.H. Ku (Ed.) Bladder Cancer (pp. 659-673). London, UK: Academic Press/Elsevier.
Dumas, J., Gargano, M.A., Dancik, G.M. (2016). shinyGEO: a web-based application for analyzing gene expression omnibus datasets. Bioinformatics, 32(23):3679-3681.
Dancik, G.M. (2015) An online tool for evaluating diagnostic and prognostic gene expression biomarkers in bladder cancer. BMC Urol, 15(1): 59.
Borah S., Xi, L., Zaug, A.J., Powell, N.M., Dancik, G.M., Cohen, S.B., et al. (2015) TERT promoter mutations and telomerase reactivation in urothelial cancer. Science, 347(6225):1006–10.
Dancik, G.M., Theodorescu, D. (2014). Robust prognostic gene expression signatures in bladder cancer and lung adenocarcinoma depend on cell cycle related genes. PLoS ONE, 9(1): e85249.
gdancik.github.io/bioinformatics/