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Related Concept Videos

Proteomics01:33

Proteomics

7.7K
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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Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Related Experiment Video

Updated: Aug 23, 2025

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Integrating Multiple Quantitative Proteomic Analyses Using MetaMSD.

So Young Ryu1, Miriam P Yun2, Sujung Kim3

  • 1School of Public Health, University of Nevada Reno, Reno, NV, USA. soyoungr@unr.edu.

Methods in Molecular Biology (Clifton, N.J.)
|October 29, 2022
PubMed
Summary
This summary is machine-generated.

MetaMSD software integrates multiple quantitative proteomics results for enhanced biomarker discovery. This tool aids researchers in combining datasets to control false discovery rates and generate new hypotheses.

Keywords:
Integrating multiple differential analysesMass spectrometry data analysisMeta-analysisProteomic softwareQuantitative proteomics

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Biostatistics

Background:

  • Quantitative proteomics generates large datasets.
  • Integrating results from multiple studies is challenging.
  • Biomarker discovery requires robust data analysis.

Conclusions:

  • MetaMSD is a valuable tool for quantitative proteomics meta-analysis.
  • It empowers researchers to leverage existing data for novel discoveries.
  • The protocol facilitates the adoption of MetaMSD in biological research.