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Related Concept Videos

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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Proteomics01:33

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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-protein Interfaces02:04

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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Pathway and network analysis in proteomics.

Xiaogang Wu1, Mohammad Al Hasan2, Jake Yue Chen3

  • 1Institute of Biopharmaceutical Informatics and Technology, Wenzhou Medical University, Wenzhou, Zhejiang Province, China; School of Informatics and Computing, Indiana University-Purdue University, Indianapolis, IN 46202, USA; Institute for Systems Biology, Seattle, WA 98109, USA.

Journal of Theoretical Biology
|June 10, 2014
PubMed
Summary
This summary is machine-generated.

Proteomics data analysis is challenging due to variability. This review categorizes tools incorporating biological function and network topology to improve insights from complex protein expression data.

Keywords:
Complex networksFunctional analysisHybrid strategyNetwork modulesPathway analysis

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Area of Science:

  • Systems biology
  • Bioinformatics
  • Computational biology

Background:

  • Proteomics studies cellular proteins and their interactions, generating vast, variable data.
  • High variability in proteomics data stems from sample prep, instruments, and analysis methods.

Purpose of the Study:

  • To review current computational tools for analyzing complex proteomics data.
  • To categorize tools based on their integration of biological function and network topology.

Main Methods:

  • Categorization of proteomics analysis tools into four types based on functional and topological information.
  • Review of tools for automated pathway module learning and network visualization.

Main Results:

  • Tools range from basic Gene Ontology (GO) analysis to integrated network analytics like PathwayExpress.
  • Identified tools that incorporate biological function and network topology for improved data interpretation.

Conclusions:

  • Categorizing tools aids in selecting appropriate methods for proteomics data analysis.
  • Further development of integrated network analytics and visualization tools is crucial for advancing proteomics research.