Michael Newton

Professor of Statistics

2120 Genetics-Biotechnology Center, newton@stat.wisc.edu, 608.263.0357

Departments

Biostatistics & Medical Informatics, Statistics

Education

PhD (1991), University of Washington, Seattle

Research Interests

Developing statistics and empirical Bayes methods in contemporary biomedical applications

Lab Website

www.stat.wisc.edu/~newton/

Representative Awards

  • 2003 Mortimer Speigelman Award
  • 2004 Presidents’ Award, Committee of Presidents of Statistical Societies
  • 2007 Elected fellow of the American Statistical Association
  • 2012 Kellett Mid-Career Research Award, University of Wisconsin-Madison

Research

Dr. Newton does research in data science for basic and translational biomedicine. His contributions span applications in cancer biology, immunology, genomics, methodologies for high-dimensional biostatistical inference, and theory for computational statistics. Dr. Newton leads a diverse, inclusive, and cutting-edge research group, with Ph.D. graduates now in leading positions in academia and industry. His lab collaborates extensively with UW Madison investigators.

Dr. Newton served on the NIH Genome study section from 2000-2004, and on the Biostatistical Methods and Research Design (BMRD) study section from 2012-2015. He is a founding editor of the Annals of Applied Statistics. At UW-Madison, Dr. Newton serves on the internal advisory committee for the Center for Human Genomics and Precision Medicine and on the steering committee for the Data Science Hub. Dr. Newton is also co-Director of the UW/NIH Center for Predictive and Computational Phenotyping (CPCP), co-PI of the UW/NSF Institute for the Foundations of Data Science (IFDS), co-PI of the NIH Funded (T32) Bio-Data Science Training Program, and co-director of the Genetics and Epigenetics Mechanisms Program in the UW Comprehensive Cancer Center.

    Representative Publications  (Google Scholar | PUBMED)

    • Zhang, H. et al. Predicting kinase inhibitors using bioactivity matrix derived informer sets. PLoS computational biology 15, e1006813, doi:10.1371/journal.pcbi.1006813 (2019).
    • Castro-Perez, E. et al. Melanoma Progression Inhibits Pluripotency and Differentiation of Melanoma-Derived iPSCs Produces Cells with Neural-like Mixed Dysplastic Phenotype. Stem Cell Reports 13, 177-192, doi:10.1016/j.stemcr.2019.05.018 (2019).
    • Pleiman, J. K. et al. The conserved protective cyclic AMP-phosphodiesterase function PDE4B is expressed in the adenoma and adjacent normal colonic epithelium of mammals and silenced in colorectal cancer. PLoS genetics 14, e1007611, doi:10.1371/journal.pgen.1007611 (2018).
    • Barger, J. L. et al. Identification of tissue-specific transcriptional markers of caloric restriction in the mouse and their use to evaluate caloric restriction mimetics. Aging Cell 16, 750-760, doi:10.1111/acel.12608 (2017).
    • Foley, T. M. et al. Dual PI3K/mTOR Inhibition in Colorectal Cancers with APC and PIK3CA Mutations. Mol Cancer Res 15, 317-327, doi:10.1158/1541-7786.MCR-16-0256 (2017).
    • Henderson, N. C. & Newton, M. A. Making the cut: improved ranking and selection for large-scale inference. J R Stat Soc Series B Stat Methodol 78, 781-804, doi:10.1111/rssb.12131 (2016).