The ABML module is a new addition to the P30-supported core. The development of this module was prompted by a survey of our supported faculty which overwhelmingly indicated a need for analytical and computational support. Our faculty generate a tremendous amount of data from a variety of sources, including de-identified medical records, imaging (retinal, tissue, brain MRI and connectivity imaging), neuro- and electrophysiological recordings from members of our cortical vision faculty, performance-based measures, molecular data from metabolomic, 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. A primary goal is to provide high-level analytical guidance and promote new collaborations between data-generating and analytical scientists, leading to advances and innovations in data manipulation and interpretation. An additional goal is to provide cutting-edge analytic approach to the researchers, including the use of AI to make theoretical and clinical predictions based on existing databases and to identify gaps in the scientific domain for leveraging new scientific methodologies. These approaches will enhance currently funded projects and stimulate project development for funding and discovery. Personnel include faculty in Ophthalmology (Ash, Sahel, Behrmann, Vupparaboina, Bollepalli) along with faculty in Biostatistics (Chen, Ding).
Contact PD/PI: Ash, John DeWayne at ashj@pitt.edu