Dr. Newton studies theory, methodology, and application of statistical inference in the biological sciences. Cancer biology has been the source of many recent applied problems, such as linkage analysis to localize genes conferring resistance or susceptibility in rat mammary cancer, and signal identification in cytogenetic or molecular data on cancer genome abnormalities. Problems from microarray expression data are of current interest. Dr. Newton has also contributed to statistical problems in the phylogenetic analysis of molecular sequences. Computational problems have been a focus of his research; he has contributed to the implementation of Markov chain Monte Carlo methods for Bayesian analysis and to the implementation and theory of bootstrap sampling. Further, Dr. Newton has developed new methods of nonparametric Bayesian analysis.
Selected Publications
For an up-to-date listing of Michael Newton's Publications, see his main page.
Courses Taught
For an up-to-date listing of Courses Taught by Michael Newton, see his main page.
