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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: Aug 16, 2025

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

Benchmarking tools for detecting longitudinal differential expression in proteomics data allows establishing a robust

Tommi Välikangas¹, Tomi Suomi¹, Courtney E Chandler²

¹Turku Bioscience Centre, University of Turku and Åbo Akademi University, FI-20520, Turku, Finland.

Nature Communications

|December 22, 2022

Summary

A new method called Robust longitudinal Differential Expression (RolDE) effectively analyzes noisy, longitudinal proteomics data. RolDE is tolerant to missing values and reproducible, making it ideal for complex biological studies.

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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
Bioinformatics
Systems Biology

Background:

Quantitative proteomics is a key tool in biological research.
Longitudinal proteomics experiments are increasingly common but lack effective analysis methods.
Existing methods struggle with noisy data, missing values, and limited replicates typical in longitudinal studies.

Purpose of the Study:

To evaluate existing differential expression methods for longitudinal omics data.
To introduce a novel, robust method for analyzing longitudinal proteomics data.
To provide a user-friendly tool for researchers.

Main Methods:

Comprehensive evaluation of multiple differential expression methods.
Development and application of the Robust longitudinal Differential Expression (RolDE) approach.
Testing on over 3000 simulated and three large experimental proteomics datasets.

Main Results:

RolDE demonstrated superior performance compared to existing methods.
RolDE exhibits high tolerance to missing values and excellent reproducibility.
The method effectively ranks results in a biologically meaningful manner.

Conclusions:

RolDE is a robust and effective method for differential expression analysis in longitudinal proteomics.
The approach is suitable for various data types and can be used by researchers with limited experience.
RolDE addresses a critical need for analyzing complex, time-series omics data.