Inferring Single Cell Profiles from Histology and Generating Omics Data from Images

Explore cutting-edge research in computational biology through two presentations from the Models, Inference and Algorithms seminar series at the Broad Institute. Delve into Charles Comiter's work on SCHAF (Single-Cell omics from Histology Analysis Framework), which uses adversarial machine learning to generate spatially resolved single-cell omics datasets from H&E histology images. Learn how this innovative approach bridges the gap between molecular-level single-cell profiling and tissue-level histology imaging, offering new insights into cell and tissue biology in health and disease. Then, discover Jian Shu's Image2Omics project, which aims to develop novel experimental and computational frameworks for generating omics data from various imaging modalities. Understand how this research could revolutionize genomic monitoring by enabling non-destructive, low-cost, and scalable methods for predicting genomic information from images, potentially leading to more generalizable machine learning methods for translating biological data.