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
  • Linh Huynh
  • Annie Lu
  • Luomeng Tan
  • Mary Agopian
  • Gergely Pap
  • Yahan Zhang
  • Natalia Mukhina


  • 2024-03-18: Michael presents a selected talk on "Human papillomavirus integration transforms chromatin to drive oncogenesis" at RECOMB-CCB 2024.
  • 2024-03-01: Isaiah is a recipient of the 2024 T-CAIREM Summer Research Program award.
  • 2024-01-08: Coby and Michael are co-authors on "Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet", an article that has been published in Genome Biology.
  • 2024-01-01: Yahan Zhang joined the Hoffman lab as a PhD student.
  • 2023-10-27: Michael is a member of PRiME - Precision Medicine Initiative that was established at the University of Toronto to align research efforts in the area of Precision Medicine
  • 2023-11-06: Eric releases Genomedata 1.7.2
  • News archive


  • Twitter: @michaelhoffman
  • LinkedIn: michaelmhoffman