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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: Dec 21, 2025

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Published on: April 19, 2019

Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling.

Tong Zhang¹, Matthew J Gaffrey¹, Matthew E Monroe¹

¹Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Journal of Proteome Research

|May 15, 2020

Summary

This summary is machine-generated.

A new block design with common references enables large-scale label-free quantitative proteomics. This method minimizes instrument drift, ensuring reproducible protein quantification across numerous samples and large datasets.

Keywords:

block design common references label-free quantification large-scale mass spectrometry quantitative proteomics

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Last Updated: Dec 21, 2025

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Published on: April 19, 2019

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

Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions

Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions

Published on: October 20, 2020

Area of Science:

Proteomics
Analytical Chemistry
Biotechnology

Background:

Label-free quantitative proteomics is valuable for global protein profiling.
Instrument performance drift in LC-MS limits large-scale sample analysis.
Variability in LC-MS platforms hinders reproducible proteomic studies.

Purpose of the Study:

To develop a robust experimental and data analysis scheme for large-scale label-free quantification.
To address the limitations of instrument drift and variability in LC-MS platforms.
To enable reproducible proteomic profiling of extensive sample cohorts.

Main Methods:

Implementation of a block design with common reference samples within each block.
Analysis of large sample sets (>100 samples) in smaller, manageable blocks.
Normalization across blocks using common reference samples for data correction.

Main Results:

Successfully profiled proteome response of 116 human macrophage samples to nanomaterials.
Achieved average coverage of 4500 proteins per sample across six blocks.
Quantified 2537 proteins with high reproducibility and consistent abundances across blocks without imputation.

Conclusions:

The developed block design with common references ensures robust and reproducible large-scale label-free proteomic quantification.
The method effectively minimizes instrument drift and inter-block variability.
This streamlined workflow is adaptable for various large cohort studies requiring accurate proteomic analysis.