# A Proteogenomic Search Engine for Direct Mass Spectrometric Identification of Variant Proteins Using Genomic Data

> **NIH NIH R44** · SPECTRAGEN INFORMATICS, LLC · 2021 · $550,206

## Abstract

Project Summary / Abstract
Mass spectrometry-based proteomics, used in conjunction with genomics, has been called proteogenomics.
Recent exponential increases in variant identification by next-generation sequencing (NGS) is redefining the
concept of the human genome/proteome. Our project is the commercialization of a first-to-market proteomic
database search engine for mass spectrometry capable of directly reading NGS data for the identification of
mutilations from individual samples or from curated resources. Such an offering has the potential to bring
together these two fields, enabling validation of mutations at the protein-level. Mutated proteins have been
shown to make ideal targets for drug therapies and diagnostics in cancer. Our software will provide an intuitive
user experience, approachable by scientists who may not be expert both proteomic and genomic data
analysis. Since the search engine is guided by prior knowledge, performance exceeds current practice. The
software will come complete with a full array of post-processing validation, and visualization tools.

## Key facts

- **NIH application ID:** 10259859
- **Project number:** 5R44CA217432-03
- **Recipient organization:** SPECTRAGEN INFORMATICS, LLC
- **Principal Investigator:** Paul Anthony Rudnick
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $550,206
- **Award type:** 5
- **Project period:** 2017-09-01 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10259859

## Citation

> US National Institutes of Health, RePORTER application 10259859, A Proteogenomic Search Engine for Direct Mass Spectrometric Identification of Variant Proteins Using Genomic Data (5R44CA217432-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10259859. Licensed CC0.

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