Last Name:

Ross

First Name:

Douglas

Visiting Investigator
Brief Bio:

Douglas T. Ross is chief scientific officer and co-founder of Applied Genomics Inc. He obtained his M.D. and Ph.D. in pathology from the University of Washington in 1994 while studying at the Fred Hutchinson Cancer Research Center and did pathology training including serving as chief resident of laboratory medicine at the University of California at San Francisco. For his postdoctoral fellowship, he joined the then-emerging microarray project at Stanford University. As part of the team that initiated and scaled-up the human cDNA microarray gene expression profiling project he helped develop strategies for large-scale analysis of gene expression in human cancer. Ross then co-founded Applied Genomics Inc., one of the HudsonAlpha resident associate companies. AGI developed a process whereby complex gene expression data is used to target antibody production and generate datasets of protein expression across thousands of tumor tissues. The company is using these reagents and datasets to reveal a novel approach towards classification of cancer with great potential to account for the clinical variation among patients that clinicians have observed for decades.

Douglas T. Ross is chief scientific officer and co-founder of Applied Genomics Inc. He obtained his M.D. and Ph.D. in pathology from the University of Washington in 1994 while studying at the Fred Hutchinson Cancer Research Center and did pathology training including serving as chief resident of laboratory medicine at the University of California at San Francisco. For his postdoctoral fellowship, he joined the then-emerging microarray project at Stanford University. As part of the team that initiated and scaled-up the human cDNA microarray gene expression profiling project he helped develop strategies for large-scale analysis of gene expression in human cancer. Ross then co-founded Applied Genomics Inc., one of the HudsonAlpha resident associate companies. AGI developed a process whereby complex gene expression data is used to target antibody production and generate datasets of protein expression across thousands of tumor tissues. The company is using these reagents and datasets to reveal a novel approach towards classification of cancer with great potential to account for the clinical variation among patients that clinicians have observed for decades.

Research Interests:

Immunohistochemistry applications for classification of cancer samples, particularly for prognosis

Cancer biology