- Massachusetts Institute of Technology, Cambridge, MA, U.S., PhD in Computational Neuroscience, 2002.
- University of Toronto, BSc in Computer Science, 1996.
- Department of Molecular Genetics, University of Toronto.
- Department of Computer Science, University of Toronto.
MY RESEARCH OVERVIEW
Morris Lab uses machine learning and statistical modeling to help decode the human genome. Currently, we are focused on two core research areas: deciphering the regulatory code for gene expression and predicting the biological function of genes and proteins. We work in close collaboration with experimental biologists to generate in vitro and in vivo data that we use to fit our models as well as to test and refine our in silico predictions.
Currently, we are building a comprehensive atlas of the binding preferences of DNA- and RNA-binding proteins and are using this atlas, along with comparative genomics and RNA expression data, to identify conserved vertebrate enhancer sequences and microRNA targets and other cisregulatory mRNA elements that influence mRNA expression, localization, stability and splicing.
Our work on gene function prediction has lead to the development of the GeneMANIA prediction server.
- PhyloWGS: reconstructing subclonal composition and evolution from whole-genome sequencing of tumors. Deshwar AG, Vembu S, Yung CK, Jang GH, Stein L, Morris Q. Genome Biol. 2015 Feb 13;16:35.
GeneMANIA: Fast gene network construction and function prediction for Cytoscape. Montojo J, Zuberi K, Rodriguez H, Bader GD, Morris Q. F1000Res. 2014 Jul 1;3:153.
Network Assessor: an automated method for quantitative assessment of a network's potential for gene function prediction. Montojo J, Zuberi K, Shao Q, Bader GD, Morris Q. Front Genet. 2014 May 16;5:123.
View Pubmed search of Dr. Morris' full list of publications.