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Related Concept Videos

Proteomics01:33

Proteomics

9.9K
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...
9.9K

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Related Experiment Video

Updated: Feb 22, 2026

Author Spotlight: Advancing the Analysis of Plasma Extracellular Vesicle Proteome for Cardiovascular Biomarker Studies
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Author Spotlight: Advancing the Analysis of Plasma Extracellular Vesicle Proteome for Cardiovascular Biomarker Studies

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Revisiting biomarker discovery by plasma proteomics.

Philipp E Geyer1,2, Lesca M Holdt3, Daniel Teupser3

  • 1Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.

Molecular Systems Biology
|September 28, 2017
PubMed
Summary

Mass spectrometry-based proteomics enables deep plasma proteome profiling. A new "rectangular" strategy correlates large cohort proteome patterns with health and disease phenotypes for improved biomarker discovery.

Keywords:
biomarkersdiagnosticmass spectrometryplasma proteomicssystems medicine

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Area of Science:

  • Biochemistry
  • Proteomics
  • Clinical Diagnostics

Background:

  • Blood biomarkers are crucial for patient categorization and treatment decisions in clinical diagnostics.
  • Current biomarkers are limited in scope, specificity, and development rate.
  • Mass spectrometry (MS)-based proteomics offers advanced capabilities for in-depth plasma proteome characterization.

Purpose of the Study:

  • To propose a novel

Main Methods:

  • Implementing a

Main Results:

  • The proposed strategy facilitates comprehensive plasma proteome profiling.
  • This approach enables the correlation of proteomic patterns with health and disease phenotypes in large cohorts.

Conclusions:

  • The