# Omics Core

> **NIH NIH P50** · UNIVERSITY OF LOUISVILLE · 2020 · $459,749

## Abstract

Abstract: 
The primary function of Omics Core is to provide members of the ULARC with the expertise, resources and 
facilities needed for metabolomic, proteomic and bioinformatic analyses of biological samples collected to 
study liver injury, nutrition, gut:liver interactions, and liver:environment/toxicant/drug interactions. OMICS Core 
personnel will assist with the design of sample collection protocols, will drive the development and the 
execution of novel and robust chromatographic methods for sample separation and mass spectrometric 
methods for the analysis of proteins, peptides, and metabolites with a goal of providing a greater 
understanding of the evolution of molecular mechanisms that correlate with or participate in liver dysfunction. 
The core will ensure uniformity and standardization in sample preparation, method development, instrument 
performance, data collection, data reporting and data sharing. The Core endeavors to contribute to the overall 
success and utility of the ULARC and to enhance the infrastructure and the technical and academic capabilities 
of the institution as a whole. In addition to its function as a service core, we will also promote the education and 
training of the ULARC members with regards to state-of–the-art Omics and Bioinformatics methods; with 
particular attention to the ULARC junior investigators.

## Key facts

- **NIH application ID:** 9917668
- **Project number:** 5P50AA024337-05
- **Recipient organization:** UNIVERSITY OF LOUISVILLE
- **Principal Investigator:** Xiang Zhang
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $459,749
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9917668

## Citation

> US National Institutes of Health, RePORTER application 9917668, Omics Core (5P50AA024337-05). Retrieved via AI Analytics 2026-06-14 from https://api.ai-analytics.org/grant/nih/9917668. Licensed CC0.

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