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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...

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
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Updated: May 11, 2026

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

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

Published on: April 18, 2025

Using R and Bioconductor for proteomics data analysis.

Laurent Gatto¹, Andy Christoforou

¹Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK.

Biochimica Et Biophysica Acta

|May 23, 2013

Summary

This summary is machine-generated.

This review highlights the utility of R, a statistical programming language, for reproducible proteomics data analysis. It guides users on finding R software and showcases applications in data handling, quality control, and quantitative analysis.

Keywords:

Data analysis statistics Mass spectrometry Quality control Quantitative proteomics Software

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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

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Last Updated: May 11, 2026

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

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

Published on: April 18, 2025

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

Area of Science:

Proteomics
Bioinformatics
Computational Biology

Background:

The increasing volume and complexity of proteomics data necessitate robust analytical tools.
Reproducibility and sound statistical practices are crucial for reliable proteomics research.
The R programming environment offers powerful capabilities for statistical analysis and data visualization.

Purpose of the Study:

To provide a comprehensive overview of using R for proteomics data analysis.
To guide researchers in selecting and utilizing appropriate R packages for proteomics.
To demonstrate practical applications of R in various stages of proteomics data analysis.

Main Methods:

Review of R programming language features relevant to data analysis.
Emphasis on R packages and their application in proteomics.
Illustrative use cases covering data input/output, quality control, and quantitative proteomics.
Provision of code examples and documentation through the RforProteomics companion package.

Main Results:

R and its add-on packages are presented as premium software for reproducible proteomics data analysis.
Practical examples demonstrate R's effectiveness in handling diverse proteomics data challenges.
The RforProteomics package serves as a valuable resource for implementing the discussed methods.

Conclusions:

R offers a flexible and powerful environment for advanced proteomics data analysis.
Adoption of R can enhance the reproducibility and rigor of proteomics studies.
The RforProteomics package facilitates the practical implementation of R in the field.