Hoffman research group

Michael M. Hoffman

We develop machine learning techniques to better understand chromatin biology. These models and algorithms transform high-dimensional functional genomics data into interpretable patterns and lead to new biological insight.


  • Segway: semi-automated genomic annotation
  • Segtools: segmentation analysis and graphics
  • Genomedata: efficient storage and retrieval
  • Umap and Bismap: tools for quantifying mappability of the genome and methylome
  • BEHST: biological enrichment of hidden sequence targets
  • Virchip: predicting transcription factor binding by learning from the transcriptome
  • PeaKO: finding transcription factor binding motifs using knockout controls


  • DNAmod: the DNA modification database


Meet the team

  • Michael Hoffman
  • Eric Roberts
  • Coby Viner
  • Mehran Karimzadeh
  • Jai Sood
  • Mickael Mendez
  • Rachel Chan
  • Danielle Denisko
  • Francis Nguyen
  • Samantha Wilson
  • Matthew McNeil
  • Yi Nian (Jeffrey) Niu
  • Siddharth Reed
  • Yushan (Ida) Liu
  • Michael Wrana
  • Natalia Mukhina


  • 2020-09-04: Michael is promoted to Senior Scientist at the Princess Margaret Cancer Centre, Toronto ON, Canada.
  • 2020-09-04: Michael is a member of the Centre for Machine Learning in Medicine, University of Toronto.
  • 2020-09-02: Eric releases Segway 3.0.2.
  • 2020-08-24: Zhiyuan (Annie) Lu was awarded the Mitacs Research Training Award (RTA).
  • 2020-08-16: Michael is an invited speaker to present at CANSSI Ontario: International Data Science Speaker Series at the University of Toronto, December 2020.
  • 2020-08-13: Coby was awarded a Canada Graduate Scholarships Michael Smith Foreign Study Supplement.
  • News archive


  • Twitter: @michaelhoffman
  • LinkedIn: michaelmhoffman