# Joint Bioinformatics and Computational Core of the MARC

> **NIH NIH P30** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2021 · $164,432

## Abstract

JOINT BIOINFORMATICS AND COMPUTATIONAL CORE ABSTRACT
The Joint Bioinformatics and Computational Core (JBC) will provide unique computational tools and analysis
that enables integration of complex multi-dimensional datasets related to arthritis and the microenvironment.
Most academic institutions provide standard analytic assistance with `omics data, such as RNA-seq. However,
future studies will require much more computational power to combine many data types, including genomics,
epigenomics, imaging and clinical information. The Core has unique expertise that leverages the biologic
insights and the computational skills of the co-directors to provide insights into disease pathogenesis. This will
be accomplished by 1) providing consultation and design assistance so that investigators can generate high
quality and interpretable data; 2) using UCSD-developed algorithms and computational methods that integrate
multi-dimensional datasets derived from diverse technologies; and 3) using systems biology to provide deeper
understanding of disease pathogenesis through the development genomic networks. The services will allow
MARC investigators to maximize the value of their research through unbiased data analysis and identification
of non-obvious targets for biologic validation.

## Key facts

- **NIH application ID:** 10254254
- **Project number:** 5P30AR073761-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** GARY S FIRESTEIN
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $164,432
- **Award type:** 5
- **Project period:** 2018-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10254254

## Citation

> US National Institutes of Health, RePORTER application 10254254, Joint Bioinformatics and Computational Core of the MARC (5P30AR073761-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10254254. Licensed CC0.

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