Computational Ophthalmology and Biomedical Informatics

NIH RePORTER · NIH · P30 · $137,458 · view on reporter.nih.gov ↗

Abstract

ABSTRACT Computational Ophthalmology and Biomedical Informatics Core The Computational Ophthalmology and Biomedical Informatics Core provides high-performance computing resources and state-of-the-art custom computer programming to UCSD vision researchers completing cellular, animal, and human vision research studies. The data analysis requirements of the vision research community are increasing exponentially as high-resolution retinal imaging datasets become the standard, genomics research utilizes exome and whole genome sequencing, and the widespread digitization of healthcare and adoption of electronic health records (EHRs) and other health information technology tools have expanded the volume of clinical data. The powerful GPU computational condo clusters managed by the San Diego Supercomputer Center, an Amazon Web Services cloud-based data management pipeline, custom software tools, and EHR data extraction and analysis services provided by this core facilitate analysis of these large datasets. The Computational Ophthalmology and Biomedical Informatics core also supports multiple computational data scientists with expertise in image analysis and signal processing expertise, big-data analytics, artificial intelligence (AI)/machine learning (ML), relational databases, and natural language processing to support computational analyses of both basic science and clinical vision research projects. In addition, essential IT services such as automated off-site backup, fileservers for secure file-sharing and institutional software licenses (FilemakerPro, Github, FreezerPro) are provided by the Computational Ophthalmology and Biomedical Informatics Core to the UCSD vision research community.

Key facts

NIH application ID
10709404
Project number
2P30EY022589-11
Recipient
UNIVERSITY OF CALIFORNIA, SAN DIEGO
Principal Investigator
LINDA M ZANGWILL
Activity code
P30
Funding institute
NIH
Fiscal year
2023
Award amount
$137,458
Award type
2
Project period
2023-09-01 → 2028-04-30