Hoffman research group
- Michael M. Hoffman
- Scientist (principal investigator)
- Research
- Princess Margaret Cancer Centre
- University Health Network
- Assistant 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
Databases
- DNAmod: the DNA modification database
Join the lab
People
Meet the team- Michael Hoffman
- Eric Roberts
- Coby Viner
- Mehran Karimzadeh
- Jai Sood
- Mickael Mendez
- Rachel Chan
- Danielle Denisko
- Francis Nguyen
- Lee Zamparo
- Samantha Wilson
- Matthew McNeil
News
- 2019-01-03: Michael is an invited speaker at Pacific Symposium on Biocomputing (PSB) 2019 in Kohala Coast, Hawaii, USA. His talk covers: "Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet".
- 2018-11-26: Michael is an invited speaker at a special seminar jointly hosted by the School of Computing and the Department of Biomedical and Molecular Sciences at Queen's University, Kingston, Ontario. His talk covers: "Identifying transcription factor binding using open chromatin, transcriptome, and methylation data".
- 2018-11-14: Michael is a co-author on "Sensitive tumour detection and classification using plasma cell-free DNA methylomes" in Nature.
- 2018-11-07: Michael is an invited speaker and co-chair of the Biological Data Science conference at Cold Spring Harbor Laboratory, New York, USA. His talk covers: "Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome".
- 2018-11-04: Michael is an invited speaker and co-chair of the Probabilistic Modeling in Genomics conference at Cold Spring Harbor Laboratory, New York, USA. His talk covers: "Segway and the Graphical Models Toolkit: a framework for probabilistic genomic inference".
- 2018-10-18: The final version of Francis and Michael's review on "Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities" in Information Fusion is now available online.
- News archive
Contact
- Twitter: @michaelhoffman
- LinkedIn: michaelmhoffman