Hoffman research group

Michael M. Hoffman
Senior Scientist (principal investigator)
Research
Princess Margaret Cancer Centre
University Health Network

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
Leo Li
Annie Lu
Esther Yoo
Natalia Mukhina

News

2021-01-15: The paper "Functional annotation of human long noncoding RNAs using chromatin conformation data" is now released on the bioRxiv preprint server.
2021-01-25: Eric releases Segway 3.0.3.
2021-01-14: Michael is an invited speaker to present his talk "Segway and the Graphical Models Toolkit: a framework for probabilistic genomic inference" at the University of Toronto Machine Intelligence Student Team (UTMIST) Talk Series.
2021-01-11: Eric releases Genomedata 1.5.0.
2021-01-08: Michael is an invited speaker to present at the Sanford Burnham Prebys Cancer Center Seminar Series on June 14, 2021.
2021-01-08: Michael is an invited speaker to present his talk "Predicting transcription factor binding and the effects of viral integration" at the Ludwig Institute Seminar Series, University of Oxford, UK on March 18, 2021.
News archive

Contact

Twitter: @michaelhoffman
LinkedIn: michaelmhoffman