The CM4AI data generation project seeks to map the spatiotemporal architecture of human cells and use these maps toward the grand challenge of interpretable genotype-phenotype learning. In genomics and precision medicine, machine learning models are often “black boxes,” predicting phenotypes from genotypes without understanding the mechanisms by which such translation occurs. To address this deficiency, project will launch a coordinated effort involving three complementary mapping approaches – proteomic mass spectrometry, cellular imaging, and genetic perturbation via CRISPR/Cas9 – creating a library of large-scale maps of cellular structure/function across demographic and disease contexts.
Who We Are

Contact Primary Investigator
University of California San Diego

Primary Investigator
Simon Fraser University

Primary Investigator
University of Alabama at Birmingham

Primary Investigator
University of Virginia

Primary Investigator
University of California San Francisco

Primary Investigator
Stanford University

Primary Investigator
University of California San Diego

Primary Investigator
University of Montreal

Primary Investigator
Yale University

Co-PI
Yale University

Co-PI
University of Texas at Austin

Co-PI
University of Virginia

Co-PI
University of California San Francisco