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Related Concept Videos

Proteomics01:33

Proteomics

7.5K
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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Protein Networks02:26

Protein Networks

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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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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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Bioinformatic analysis of proteomics data.

Andreas Schmidt, Ignasi Forne, Axel Imhof

    BMC Systems Biology
    |July 18, 2014
    PubMed
    Summary
    This summary is machine-generated.

    Identifying and analyzing cellular proteins is crucial for understanding cell function. This study discusses strategies for gathering, filtering, and analyzing proteomic data using software to generate new biological hypotheses.

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    Area of Science:

    • Biochemistry
    • Molecular Biology
    • Proteomics

    Background:

    • Cellular phenotypes are primarily determined by specialized regulatory proteins.
    • Understanding molecular processes requires identifying, quantifying, and characterizing all cellular proteins.

    Purpose of the Study:

    • To discuss current strategies for analyzing proteomic data.
    • To enable the generation of testable hypotheses from existing biological information.

    Main Methods:

    • Utilizing robust and reliable mass spectrometry for complex protein mixture analysis.
    • Employing available software packages for data gathering, filtering, and analysis.

    Main Results:

    • Systematic analysis of all cellular proteins is now feasible due to advancements in mass spectrometry.
    • Standardized methods are needed for analyzing proteomic data to generate new hypotheses.

    Conclusions:

    • Effective proteomic data analysis is essential for advancing our understanding of cellular physiology.
    • The development of standardized analytical methods will facilitate hypothesis generation in biological research.