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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: Jun 13, 2025

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Published on: April 1, 2017

ProteoPlotter: An Executable Proteomics Visualization Tool Compatible with Perseus.

Esther Olabisi-Adeniyi¹, Jason A McAlister¹, Daniela Ferretti²

¹Molecular and Cellular Biology, University of Guelph, Guelph, Ontario N1G 2W1, Canada.

Journal of Proteome Research

|May 13, 2025

Summary

This summary is machine-generated.

ProteoPlotter enhances proteomics data visualization for researchers. This tool complements Perseus, offering advanced plotting features for deeper biological insights from complex mass spectrometry data.

Keywords:

1D annotation enrichment Klebsiella pneumoniae Perseus UpSet plots Venn diagrams data visualization dynamic range heat maps proteomics volcano plots

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Last Updated: Jun 13, 2025

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Published on: April 1, 2017

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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

Published on: May 22, 2018

Area of Science:

Proteomics
Bioinformatics
Computational Biology

Background:

Mass spectrometry-based proteomics generates complex data requiring robust statistical analysis and visualization.
Existing tools like Perseus are widely used but have room for improved visualization and data accessibility.
Effective visualization is crucial for drawing meaningful conclusions from large-scale proteomics datasets.

Purpose of the Study:

To develop ProteoPlotter, a user-friendly tool to enhance visualization of proteomics data.
To complement the Perseus platform with advanced, accessible visualization capabilities.
To facilitate deeper biological insights through improved data representation.

Main Methods:

Development of ProteoPlotter using the R programming language and Shiny framework.
Implementation of multidimensional data illustration, including 1D enrichment analyses and adaptable volcano plots.
Integration of Gene Ontology terminology and visualization of confidence intervals in PCA plots using data ellipses.

Main Results:

ProteoPlotter provides intuitive visualization of complex proteomics data, complementing Perseus.
The tool supports enhanced volcano plots with Gene Ontology integration and PCA plots with data ellipses.
Demonstrated application in analyzing microbial proteome remodeling under altered nutrient conditions.

Conclusions:

ProteoPlotter offers comprehensive and customizable visualization features for proteomics data.
The tool enhances biological discovery by linking advanced visualization with Perseus data analysis.
ProteoPlotter is designed for accessibility by both biological and computational researchers.