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Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...

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Related Experiment Video

Updated: Apr 22, 2026

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

Published on: January 10, 2025

Flexible and accessible workflows for improved proteogenomic analysis using the Galaxy framework.

Pratik D Jagtap¹, James E Johnson, Getiria Onsongo

¹Center for Mass Spectrometry and Proteomics, University of Minnesota , 43 Gortner Laboratory, 1479 Gortner Avenue, St. Paul, Minnesota 55108, United States.

Journal of Proteome Research

|October 11, 2014

Summary

This summary is machine-generated.

This study introduces a Galaxy-based platform for proteogenomic analysis, integrating genomic, transcriptomic, and proteomic data. The flexible workflow enhances the discovery of protein variants and improves genome annotation for researchers.

Keywords:

customized database generation peptide corresponding to a novel proteoform peptide-spectral match evaluation proteogenomics salivary proteins workflows

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Area of Science:

Bioinformatics
Proteomics
Genomics

Background:

Proteogenomics integrates genomic, transcriptomic, and proteomic data for novel protein discovery and genome annotation.
Current proteogenomic analysis involves complex data processing steps.
A unified, accessible, and customizable software platform is needed for proteogenomic workflows.

Purpose of the Study:

To extend the Galaxy bioinformatics framework for streamlined proteogenomic analysis.
To demonstrate the flexibility and utility of a customized Galaxy workflow for proteogenomic research.
To provide a blueprint for a standardized proteogenomic analysis platform.

Main Methods:

Extension of the Galaxy bioinformatics framework.
Development of a modular workflow incorporating established and custom software tools.
Implementation of automated BLASTP searching and a Peptide Sequence Match Evaluator.

Main Results:

Demonstrated improved depth and quality of proteogenomic results using human saliva data.
Successfully created a complex, modular workflow (approx. 140 steps) within Galaxy.
Developed custom tools for evaluating peptide identification veracity.

Conclusions:

The customized Galaxy framework provides a flexible and accessible solution for proteogenomic analysis.
The developed workflow enhances the discovery of protein sequence variants and genome annotation.
Galaxy is well-suited to become an ideal platform for the emerging field of proteogenomics.