Michael Hoffman, PhD Scientist, Princess Margaret Cancer Centre, Assistant Professor, Departments of Medical Biophysics and Computer Science, University of Toronto Faculty Affiliate, Vector Institute

Michael Hoffman creates predictive computational models to understand interactions between genome, epigenome, and phenotype in human cancers. He implemented the genome annotation method Segway, which simplifies interpretation of large multivariate genomic datasets, and was a linchpin of the NIH ENCODE Project analysis. He was named a CIHR New Investigator and has received several awards for his academic work, including the NIH K99/R00 Pathway to Independence Award, and the Ontario Early Researcher Award.

Website: http://hoffmanlab.org/

Location: Toronto

Interests:

Cancer

ChIP-seq

Chromatin

DNase-seq

Dynamic Bayesian networks

Epigenomics

Functional genomics

Graphical models

Machine learning