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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 proteomics...

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Related Experiment Video

Updated: Jul 4, 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

PepSeeker: mining information from proteomic data.

Jennifer A Siepen¹, Julian N Selley, Simon J Hubbard

¹Faculty of Life Sciences, The University of Manchester, Manchester, UK, Michael Smith Building.

Methods in Molecular Biology (Clifton, N.J.)

|July 2, 2008

Summary

This summary is machine-generated.

Proteomics generates vast datasets. This study shows how the PepSeeker resource mines proteomic data for improved peptide identification algorithms by analyzing how peptides fragment in mass spectrometers.

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Published on: November 15, 2017

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Last Updated: Jul 4, 2026

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

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Published on: January 10, 2025

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

Area of Science:

Proteomics
Analytical Chemistry
Bioinformatics

Background:

Proteomics is a rapidly advancing field driven by mass spectrometry and genomics.
High-throughput proteomics generates large datasets requiring robust storage and exchange solutions.
Effective data management is crucial for sharing findings and enabling cross-laboratory comparisons.

Purpose of the Study:

To demonstrate the utility of the PepSeeker resource for mining proteomic data.
To enhance peptide identification algorithms through a deeper understanding of peptide fragmentation.
To support data exchange and analysis within the proteomics community.

Main Methods:

Utilizing the PepSeeker resource to analyze proteomic data.
Investigating peptide fragmentation patterns within mass spectrometers.
Applying insights to improve peptide identification algorithms.

Main Results:

PepSeeker effectively mines valuable information from complex proteomic datasets.
Understanding peptide fragmentation enhances the accuracy of peptide identification.
The approach facilitates better data sharing and analysis across different platforms.

Conclusions:

Proteomics is a mature field generating rich, complex datasets.
Resources like PepSeeker are essential for managing and extracting insights from proteomic data.
Improved understanding of fragmentation mechanisms can significantly advance peptide identification.