The QUON-titative computational biology lab at UC Davis focuses on developing and applying methods from machine learning and statistics to unravel the genetic basis of complex traits and diseases such as Alzheimer’s and cancer. Some examples of our research include ways to integrate heterogeneous data (genetic, epigenetic, transcriptional) to model how transcriptional regulatory networks change over time and with disease progression, predict which combinations of drugs are optimal for targeting specific cell types and cancer types, and predict how variation in genetics and environmental exposures interact to change our risk of developing complex diseases.
We have open positions in our lab for both students and postdocs! Contact Gerald Quon at email@example.com for more details.
Gerald Quon is an Assistant Professor at the University of California, Davis. Previously, he was a postdoc in the Computational Biology Group at MIT and the Broad Institute, building models to predict the mechanism of action of genetic variants associated with type 2 diabetes, total cholesterol and Alzheimer’s Disease. He completed his PhD in Computer Science at the University of Toronto under Quaid Morris, where his research focused on developing models to deconvolute gene expression profiles of heterogeneous cell populations, in order to improve personalized medicine in cancer. He also holds a MSc in Biochemistry from the University of Toronto, as well as an undergraduate degree in Computer Science from the University of Waterloo.