SUMMARY – ANALYTICS, BIOSTATISTICS, AND MACHINE LEARNING MODULE The Analytics, Biostatistics, and Machine Learning (ABML) module integrates expertise in the Departments of Ophthalmology, Pediatrics, and Biostatics in an innovative approach to create access to modern computational analysis of integrated datasets. Our participating faculty generate a tremendous amount of data from a variety of sources, including de-identified medical records, retinal imaging, tissue imaging, physiological recordings from members of our cortical vision faculty, performance-based tests, molecular data from metabolomics, microbiome, RNA-Seq, ATAC-Seq, single-cell/nuclei RNA- and ATAC-Seq, and ChIP-Seq. The ABML module will connect people generating data with module personnel who are experts in biostatistics, statistical modeling, machine learning, and deep learning methodologies. The overall goal is to provide high-level analytical guidance, accelerate and enhance research discovery, and promote new collaborations between data-generating and analytical scientists. Modular activities will also be available for the training of our students and postdocs and increasing synergistic interactions between the P30 participating faculty.