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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: Jun 10, 2026

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

Statistical methods for proteomics.

¹Department of Medical Statistics, Georg-August-University Göttingen, Göttingen, Germany.

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

|July 24, 2010

Summary

Advancements in analytical methods now allow for the simultaneous comparison of thousands of protein expression levels in biological samples. This chapter details statistical designs and data analysis methods for proteomics experiments, focusing on two-dimensional gel electrophoresis and mass spectrometry.

Area of Science:

Proteomics and analytical biochemistry.
Bioinformatics and statistical analysis of biological data.

Background:

Significant improvements in protein and peptide detection and quantification methods over the last decade.
Enabling large-scale comparative analyses of protein expression across different biological contexts.

Purpose of the Study:

To present statistical experimental designs for high-throughput proteomics.
To illustrate data analysis methodologies for proteomics studies.
To focus on preprocessing and analysis of protein expression data from specific techniques.

Main Methods:

Statistical design of proteomics experiments.
Data analysis techniques for large-scale protein expression data.
Focus on preprocessing and analysis for two-dimensional gel electrophoresis (2D-PAGE) and mass spectrometry (MS).

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Last Updated: Jun 10, 2026

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

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

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Main Results:

The chapter provides a framework for designing and analyzing complex proteomics experiments.
It details methods applicable to data generated from 2D-PAGE and MS.
Highlights the importance of statistical rigor in interpreting large-scale proteomic data.

Conclusions:

Modern analytical techniques facilitate comprehensive proteomic profiling.
Statistical methodologies are crucial for extracting meaningful insights from complex proteomic datasets.
The presented approaches are vital for comparative studies, such as normal versus cancerous tissues.