Dr. Parisa Shooshtari
Dr. Parisa Shooshtari
Dr. Parisa Shooshtari
Early-Career Investigator


Early-Career Investigator

Dr. Shooshtari develops computational and statistical methods to understand the cellular and molecular mechanisms of diseases. 

Dr. Parisa Shooshtari received her PhD from the University of British Columbia in 2012 and went on to complete postdoctoral training at Yale University and the Broad Institute of MIT and Harvard. Most recently, Shooshtari served as a Research Associate with the Centre for Computational Medicine at the Hospital for Sick Children (SickKids). Shooshtari’s research program focuses on developing computational and statistical methods to understand cellular and molecular mechanisms underlying complex diseases. Her office and laboratory space is located within the Victoria Research Laboratories at the Victoria campus of the London Health Sciences Centre.

Experience & Education
  • Research Associate, Centre for Computational Medicine, SickKids Research Institute
  • Postdoctoral Associate, Yale University
  • Postdoctoral Scholar, Broad Institute of MIT and Harvard
  • PhD, University of British Columbia
Current Affiliations
  • Early-Career Investigator, OICR
  • Assistant Professor, Western University
  • Scientist, Children’s Health Research Institute
  • Scientist, Lawson Health Research Institute
Select Publications

See Dr. Shooshtari’s recent publications on Google Scholar.

Research Areas
Biology Informatics and Data Standards
Disease Areas
  • Ontario Institute for Cancer Research, Investigator I
  • Yale University, Five-year postdoctoral training support
  • CYTO 2011, Presidential Award for Excellence Finalist
Opportunities to Collaborate

For opportunities to collaborate with Dr. Shooshtari, please contact her directly.

Visit OICR’s Collaborative Research Resources directory for more opportunities to collaborate with OICR researchers.

  • OCHROdb: A comprehensive, quality checked database of open chromatin regions from sequencing data
  • Regfm: Regulatory fine mapping
  • SamSPECTRAL: Sampling spectral clustering