# Proteomics

> **NIH NIH P30** · UNIVERSITY OF ARIZONA · 2020 · $123,936

## Abstract

Project Summary / Abstract: Proteomics Shared Resource (PSR) 
The goal of the Proteomics Shared Resource (PSR) is to enable University of Arizona Cancer Center (UACC) 
investigators to identify and characterize proteins and peptides and their modifications using modern 
proteomics methods. The PSR provides twenty distinct proteomics services that enable the systematic 
analysis of protein identification and characterization, including quantification and mapping modifications, via 
state-of-the-art modern mass spectrometry and peripheral instrumentation. PSR equipment includes an array 
of proteomics instrumentation including 2D and 3D quadrupole ion traps, hybrid mass analyzers (Waters 
QTOF Premier and the AB Sciex 4000 QTRAP), an AB Sciex triple quadruple mass analyzer and MALDI-TOF 
mass spectrometer, and a linear quadrupole ion trap Orbitrap Velos high-resolution and high-accuracy mass 
spectrometer system with CID/HCD/ETD. All mass analyzers are full LC-MS/MS systems, with the exception of 
the MALDI-TOF system. A comprehensive set of proteomics services are offered to UACC members at very 
affordable rates. Free-of-charge unlimited assistance and consultation with experimental design, planning, data 
mining, and data interpretation are also offered to UACC members. The PSR staff provides training for users 
when requested.

## Key facts

- **NIH application ID:** 9969488
- **Project number:** 5P30CA023074-40
- **Recipient organization:** UNIVERSITY OF ARIZONA
- **Principal Investigator:** Krishna Parsawar
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $123,936
- **Award type:** 5
- **Project period:** — → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9969488

## Citation

> US National Institutes of Health, RePORTER application 9969488, Proteomics (5P30CA023074-40). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9969488. Licensed CC0.

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