PI: Michael I. Love
Assistant Professor
Department of Biostatistics
Department of Genetics
University of North Carolina-Chapel Hill

Google Scholar
Biostatistics Dept. bio

michaelisaiahlove at gmail dot com *

* for software questions, do not email, instead use the Bioconductor support site


  • March 2018 - Michael Love will give an RNA-seq tutorial at ENAR conference in Atlanta, GA: “Fast & Easy RNA-seq Computational Workflow Using Bioconductor”, Tuesday, March 27 from 8:30-10:15. He will also speak during the “Teaching Data Science at all Levels” session, Monday, March 26 from 8:30-10:15.
  • June 2018 - Michael Love will be an instructor at the Statistical Methods for Functional Genomics meeting at Cold Spring Harbor Laboratory which runs June 29 - July 12, 2018. The application deadline is March 31, 2018.
  • July 2018 - Michael Love will be an instructor at the Statistical Data Analysis for Genome Scale Biology meeting in Brixen, Italy which runs July 8-13, 2018. Registration closes May 15, 2018.


  • February 2018 - Michael Love gave a talk at UVA’s Center for Public Health Genomics: Fragment-level bias modeling for RNA-seq Data Analysis (link to Google Slides).
  • December 2017 - Anqi Zhu and Michael Love featured in a Nature article talking about the Bioconductor Project for genomic data analysis.
  • December 2016 - Michael Love gave a talk at UMD’s Computational Biology, Bioinformatics & Genomics seminar series.
  • October 2016 - Michael Love gave a talk at the Triangle Statistical Genetics Meeting, SAS Campus, Cary.


The Love Lab uses statistical models to infer biologically meaningful patterns from high-throughput sequencing data, and develops open-source statistical software for the Bioconductor Project. A major effort of the lab is maintaining the DESeq2 package for statistical analysis of RNA-seq experiments, and associated packages and workflows for analyzing genomics data.

PI - Background

From 2013-2016, I was a Postdoctoral Fellow in the group of Rafael Irizarry in the Biostatistics and Computational Biology Department at the Dana-Farber Cancer Institute and the Harvard TH Chan School of Public Health. I completed a PhD in Computational Biology and Scientific Computing (2013) in the Vingron Department at the Max Planck Institute for Molecular Genetics in Berlin and the Mathematics and Informatics Department of the Freie Universität, Berlin. I completed a Statistics M.S. (2010) and Mathematics B.S. (2005) at Stanford University.