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Erin Conlon

Associate Professor
Department of Mathematics and Statistics
Lederle Graduate Research Tower 1436
Amherst, MA 01003
Phone: (413) 545-0622
Fax: (413) 545-1801
Email: conlon _at_ math.umass.edu
http://www.math.umass.edu/~conlon



Education and Professional History

  • Postdoctoral Fellow, Department of Statistics, Harvard University
  • Visiting Scholar, Functional Genomics, Institute for Pure and Applied Mathematics (IPAM), University of California, Los Angeles
  • Postdoctoral Fellow, Statistical Genetics, University of Washington, Seattle
  • Ph.D. Biostatistics, University of Minnesota
  • M.S. Biostatistics, University of Minnesota
  • B.S. Mathematics, University of Wisconsin, Madison

Research and Collaborators

Publications
  • Data Science, Big Data and Analytics: I am currently developing Bayesian statistical methods for data science, big data and analytics, with the following researchers.

    Xiaojing Wang

    Zheng Wei

    Alexey Miroshnikov

  • Statistical Methods in Genomics and Bioinformatics: My research interests also include gene expression and DNA sequence analysis, Bayesian models for the analysis of genomic data and comparative genomics, with the following topics.

    • Climate change and systems biology. My current work focuses on climate change and systems-biology approaches to the study of regulatory and metabolic networks of microbes, in collaboration with the lab of Kristen DeAngelis. You can read about our project here.

    • Breast cancer gene expression studies. I am also working on statistical and bioinformatic methods for breast cancer gene expression studies in humans with the lab of Joseph Jerry.

    • Other projects involve the organisms Prochlorococcus marinus, Geobacter, and Bacillus subtilis, in collaboration with the labs of the following researchers.

      Jeffrey Blanchard

      Derek Lovley

      Jeffrey Townsend

      Richard Losick

Software

parallelMCMCcombine: An R package for Bayesian methods for big data and analytics

Motif Regressor: Regulatory motif discovery using gene expression information

Bayesian Meta-Analysis of Microarray Data

Teaching

Stat 516: Statistics II, Fall 2018

Stat 526: Design of Experiments, Spring 2018

Stat 516: Statistics II, Spring 2018

Stat 697B: Bayesian Statistics, Fall 2017