# Bioinformatics

> **NIH NIH P30** · UNIVERSITY OF CALIFORNIA BERKELEY · 2024 · $199,236

## Abstract

Project Summary Bioinformatics Core
Vision science, like many fields in biology, is benefitting tremendously from technological
advances that make it possible to collect huge amounts of data about genes, proteins, lipids, and
cellular structures in intact tissues of the eye and brain. Likewise, advances in functional imaging
are making it easier to collect information about activity of neurons in the retina and brain as
they are responding to visual images. While Berkeley scientists have tremendous expertise in
collecting “big data” sets, many investigators and their labs lack the knowledge, resources, and
time to organize, process, and analyze the data to reveal meaningful results. With the entry of a
new Vision Science faculty member with great expertise in Bioinformatics and the availability of
a great local labor pool of highly astute young expert Data Scientists, we have decided to
establish a new Bioinformatics Core that will provide sorely needed to services to Vision Science
faculty. The Aims of the Core are 1) to establish cloud-based pipelines for preprocessing, storage
and retrieval of high-throughput single-cell transcriptomics and imaging data, 2) develop and
maintain bioinformatic pipelines to support downstream analysis of new and publicly available
datasets, and 3) provide advisory and training services on bioinformatic methods.

## Key facts

- **NIH application ID:** 10929323
- **Project number:** 5P30EY003176-42
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** KARSTEN GRONERT
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $199,236
- **Award type:** 5
- **Project period:** 1997-08-01 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10929323

## Citation

> US National Institutes of Health, RePORTER application 10929323, Bioinformatics (5P30EY003176-42). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10929323. Licensed CC0.

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