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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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Updated: Mar 30, 2026

Quantitative Phosphoproteomics in Fatty Acid Stimulated Saccharomyces cerevisiae

Quantitative Phosphoproteomics in Fatty Acid Stimulated Saccharomyces cerevisiae

Published on: October 12, 2009

Systems Analysis for Interpretation of Phosphoproteomics Data.

Stephanie Munk¹, Jan C Refsgaard^1,2, Jesper V Olsen³

¹Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3b, Bldg. 6.1, 2200, Copenhagen, Denmark.

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

|November 21, 2015

Summary

Extracting biological meaning from large phosphoproteomics datasets requires systems-level analysis. This chapter summarizes key bioinformatics tools and critical considerations for meaningful interpretation of phosphoproteomics data.

Keywords:

Cytoscape Functional network s Gene ontology Phosphoproteomics STRING Sequence motif s Systems analysis

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Last Updated: Mar 30, 2026

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Area of Science:

Proteomics
Bioinformatics
Systems Biology

Background:

Phosphoproteomics studies generate vast datasets with numerous quantified phosphosites.
Extracting biological insights from large-scale phosphoproteomics data presents a significant challenge.

Purpose of the Study:

To summarize appropriate bioinformatics tools for systems-level analysis of phosphoproteomics data.
To highlight critical considerations for meaningful interpretation of phosphoproteomics datasets.

Main Methods:

Review and summary of existing bioinformatics tools for phosphoproteomics data analysis.
Discussion of data input requirements and interpretation strategies for systems analysis.

Main Results:

Identification of specialized databases for annotation and pathway enrichment.
Highlighting platforms for generating functional protein networks.

Conclusions:

Systems-level analysis is crucial for deriving functional insights from phosphoproteomics data.
Careful consideration of input data and critical interpretation are essential for meaningful results.