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Related Concept Videos

Proteomics01:33

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...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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Related Experiment Video

Updated: Jun 13, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
10:37

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

Statistical contributions to proteomic research.

Jeffrey S Morris1, Keith A Baggerly, Howard B Gutstein

  • 1Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.

Methods in Molecular Biology (Clifton, N.J.)
|April 22, 2010
PubMed
Summary
This summary is machine-generated.

Statistical expertise is crucial for the success of proteomic profiling studies. Proper quantitative methods ensure accurate diagnosis, prognosis, and treatment strategies for diseases.

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Last Updated: Jun 13, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames
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Area of Science:

  • Biomedical research
  • Proteomics
  • Statistical analysis

Background:

  • Proteomic profiling offers significant potential for disease diagnosis, prognosis, and treatment.
  • Current proteomic technologies generate complex data with substantial quantitative challenges.
  • Insufficient attention to quantitative aspects can compromise study outcomes and lead to invalid results.

Purpose of the Study:

  • To highlight the importance of statisticians in proteomic research.
  • To outline key statistical principles for experimental design and data analysis in proteomics.

Main Methods:

  • Review of statistical principles applicable to proteomic studies.
  • Discussion of the role of quantitative scientists in proteomic research teams.

Main Results:

  • The involvement of statisticians can significantly enhance the success of proteomic research.
  • Adherence to statistical principles is vital for robust experimental design and analysis.

Conclusions:

  • Integrating statistical expertise is essential for overcoming quantitative challenges in proteomics.
  • Sound statistical practices are fundamental for reliable proteomic profiling and its clinical applications.