Computational biologist Thomas Norman, PhD, of Memorial Sloan Kettering’s (MSK) Sloan Kettering Institute (SKI) has been named one of 53 recipients of the prestigious 2020 National Institutes of Health (NIH) Director’s New Innovator Award. As part of the award, Dr. Norman will receive $1.5 million in direct costs upfront in the first year of a five-year award.
Established in 2007, the Director’s New Innovator Award is a part of the High-Risk, High-Reward Research program, which supports highly innovative research from early stage investigators whose creativity and research has the potential to produce a major impact on broad, important problems relevant to the mission of NIH, including on topics related to behavioral, social, biomedical, applied, and formal sciences, as well as basic, translational, or clinical research.
“I’m absolutely thrilled and honored to be named a recipient of the NIH Director’s New Innovator Award,” said Dr. Norman. “I’m even more excited that the NIH is supportive of our research and is dedicated to guiding our work on gene interactions as well as our use of machine learning and single-cell genomics.”
“I am extremely thrilled that Dr. Norman is a 2020 New Innovator Award winner,” said Joan Massagué, PhD, Director of SKI. “Dr. Norman is an exceptional scientist and I believe this award will only help further the contributions he is making in computational and systems biology.”
“The breadth of innovative science put forth by the 2020 cohort of early career and seasoned investigators is impressive and inspiring,” said NIH Director Francis S. Collins, MD, PhD. “I am confident that their work will propel biomedical and behavioral research and lead to improvements in human health.”
Dr. Norman is an Assistant Member of SKI where his research focuses on how specific combinations of genes exhibit emergent properties when expressed together, enabling the generation of diverse cell types and behaviors. The challenge of studying such genetic interactions is their sheer scale: e.g., among 10,000 genes there are ~50 million possible pairwise interactions. The Norman Lab blends computational approaches with high-throughput experimental methods to develop new approaches for finding and characterizing how genetic interactions alter behavior in cancer and tissue fibrosis.
He received his bachelor’s degree in mathematics and engineering and his master’s degree in mathematics at Queen’s University in Ontario, Canada, and his PhD in systems biology from Harvard University, where he developed a microfluidic technology for monitoring the behavior of individual cells over very long periods of time. He continued his postdoctoral research as a Damon Runyon Cancer Research Foundation Fellow at the University of California, San Francisco, where he focused on new experimental methods enabled by massively parallel single-cell RNAseq, including the Perturb-seq approach for genetics.
NIH Grant Number: DP2 GM140925-01.