# Bioinformatics, data integration, and knowledge extraction from high throughput proteomics for enabling biomedical applications

> **NIH NIH P41** · BATTELLE PACIFIC NORTHWEST LABORATORIES · 2020 · $307,074

## Abstract

Project Summary – TR&D 3
The Resource overall has the goal of broadly impacting biomedical research by providing the abilities to: obtain
high quality proteomics data from much smaller samples, produce more quantitative and comprehensive
measurements, generate improved and more extensive information on low abundance components, distinguish
presently problematic peptide isomers, and enable the study of much larger sample sets than presently
practical by providing increases in measurement throughput. Advances under TR&Ds 1 and 2 in this renewal
will provide large improvements in the sensitivity, breadth, quality, and quantity (i.e. throughput) of proteome
data. The efforts of TR&D 3 will enable these capabilities through advanced algorithms for data processing and
the integration of multiple proteomics and other data sets to aid the extraction of biomedical insights. TR&D 3
will develop new algorithms for protein identification and quantification that are needed to effectively utilize
the unique capabilities of the SLIM ion mobility (IM)-MS platform developed in TR&D 2. Highly accurate and
very highly precise and reproducible collision cross section (CCS) values derived from the SLIM ultra-high
resolution IM measurements will provide more confident and sensitive identification of peptides/proteins. A
key aspect of our approach is the use of large sets of stable isotope labeled peptides for the calibration of SLIM
ultra-high resolution IM separations leading to more precise peptide collision cross section information. These
same stable isotope labeled peptide sets will also serve as calibrants to enable highly accurate quantification of
their unlabeled analogs as well as for broad quantification of all peptides and proteins at somewhat reduced
accuracy. Advances under TR&Ds 1 and 2 will also enable a broader measurement of post-translational
modifications, which we will use to infer networks and pathways active in the samples. We will continue to
develop our collaborative visual analytic tool in conjunction with these networks to facilitate exploration and
interpretation of the data. These efforts will build upon previous Resource developments and will be facilitated
by key technological developments under TR&D 2. In combination, these efforts will provide a basis for rapid
implementation and initial evaluation of new proteomics capabilities providing both larger and richer data sets
for challenging biomedical projects, as well as their effective dissemination to the research community.

## Key facts

- **NIH application ID:** 9988429
- **Project number:** 5P41GM103493-18
- **Recipient organization:** BATTELLE PACIFIC NORTHWEST LABORATORIES
- **Principal Investigator:** Samuel H Payne
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $307,074
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9988429

## Citation

> US National Institutes of Health, RePORTER application 9988429, Bioinformatics, data integration, and knowledge extraction from high throughput proteomics for enabling biomedical applications (5P41GM103493-18). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9988429. Licensed CC0.

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