Assistant Professor Kwonmoo Lee was awarded an R35 MIRA ESI Award from the National Institute of Health (NIH)/National Institute of General Medical Sciences (NIGMS) for Unraveling Subcellular Heterogeneity of Molecular Coordination by Machine Learning in the amount of $1,738,826 over the course of 5 years. The major goal of this project is to develop a novel machine learning framework for large-scale analyses of subcellular heterogeneity of cell protrusion. The project will include 1) Deconvolution of subcellular heterogeneity of protrusion and molecular coordination in live cells by integrating time-series modeling and machine learning, 2) Deep learning-based high-throughput fluorescence live cell imaging, and 3) Heterogeneity of subcellular bioenergetic status in cell protrusion. The project team includes research scientist, Hee June Choi, and MS student, Xiang Pan, along with soon to be hired postdoctoral researchers.
Professor Lee's second grant is a Department of Defense (DoD) Breast Cancer Research Program Breakthrough Award for Artificial Intelligence-based Diffraction Analysis (AIDA) for Point-of-Care Breast Cancer Classification for $592,419 over the course of 3 years. The major goal of this project is to advance the next generation imaging cytometer, AIDA, for automated molecular screening on individual cancer cells by combining in-line hologram and deep learning. A deep learning system will be developed which can reliably recognize breast cancer cells and extract important molecular information directly from inherently complex diffraction patterns from in-line holographic imaging systems. Postdoctoral researcher, Azzam Alwan and Professor Hakho Lee from MGH/Harvard Medical School will work collaboratively on this project.