# Bioinformatics Core

> **NIH NIH P50** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2023 · $155,978

## Abstract

PROJECT SUMMARY/ABSTRACT
Bioinformatics Core
The purpose of this Core is to provide bioinformatic analysis of transcriptomic data. Our Core will provide the
essential data analysis service to render this data accessible and interpretable to the members of this
consortium. The directors and staff of this Core have extensive experience in the analysis of genomic data, as
well as familiarity with the underlying biology of the associated projects. Specifically, we will process bulk,
single cell and spatial transcriptomic data using existing pipelines. Moreover, we have developed tools to
interpret transcriptomic profiles in terms of cell type and inflammatory signatures. We also have expertise in the
use of data integration tools to combine our transcriptomic data with genetic and lipidomic data. Finally, we will
provide tools for data visualization, such as an R Shiny server for viewing individual genes in two dimensional
projections of single cell transcriptomes. The Core we are proposing here will allow all the groups within this
CORT to receive analyzed data that can be directly interpreted by researchers without extensive computational
expertise. This functionality should render genomics research far more accessible to all members of this
CORT.

## Key facts

- **NIH application ID:** 10689963
- **Project number:** 5P50AR080594-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Matteo Pellegrini
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $155,978
- **Award type:** 5
- **Project period:** 2022-09-01 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10689963

## Citation

> US National Institutes of Health, RePORTER application 10689963, Bioinformatics Core (5P50AR080594-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10689963. Licensed CC0.

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