Research in the Mesirov Lab focuses on cancer genomics applying machine-learning methods to functional data derived from patient tumors. The lab analyzes these molecular data to determine the underlying biological mechanisms of specific tumor subtypes, to stratify patients according to their relative risks of relapse, and to identify candidate compounds for new treatments. The overall goal is to treat patients as individuals specific to their tumors. Importantly, the lab is committed to the development of practical, accessible software tools to bring these methods to the general biomedical research community.
Associate Vice Chancellor, Computational Health Sciences
Professor of Medicine
Bioinformatics and Systems Biology
BMI Research Area(s)
BISB Research Area(s)
Brief Research Description
Algorithms and analytic methodologies for pattern recognition and discovery with applications to cancer genomics, to better diagnose, stratify, and treat patients. Development of biologist-friendly biomedical software tools.