Hoffman research group
- Michael M. Hoffman
- Senior Scientist (principal investigator)
- Research
- Princess Margaret Cancer Centre
- University Health Network
- Associate Professor (status-only)
- Computational Biology Group
- Department of Computer Science
- University of Toronto
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.
Publications
Software
- 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
Databases
- DNAmod: the DNA modification database
Join the lab
People
Meet the team- Michael Hoffman
- Eric Roberts
- Coby Viner
- Mickael Mendez
- Samantha Wilson
- Linh Huynh
- Annie Lu
- Esther Yoo
- Luomeng Tan
- Veronica Alba
- Natalia Mukhina
News
- 2022-04-20: Michael is an invited panelist to present his talk "Acidbio and BED" at the panel "Testbeds and validation of standards", The GA4GH Connect meeting.
- 2022-04-13: Michael is an invited speaker to present his talk "Predicting transcription factor binding and the effects of viral integration" at a Computational Biology Seminar Series at the Garvan Institute of Medical Research in Sydney, Australia.
- 2022-03-14: Eric releases Segway 3.0.4
- 2021-12-16: Mickael is a member of the Data Sciences Institute (DSI) at the University of Toronto.
- 2021-12-01: Mickael and Michael are co-authors on "Automated identification of cell-type–specific genes and alternative promoters", a preprint on bioRxiv.
- 2021-11-22: Mickael and Michael are co-authors on "Unsupervised analysis of multi-experiment transcriptomic patterns with SegRNA identifies unannotated transcripts", a preprint on bioRxiv.
- News archive
Contact
- Twitter: @michaelhoffman
- LinkedIn: michaelmhoffman