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Related Concept Videos

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,...
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,...
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-protein Interfaces02:04

Protein-protein Interfaces

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 polypeptide...
Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...

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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

ITM Probe: analyzing information flow in protein networks.

Aleksandar Stojmirović1, Yi-Kuo Yu

  • 1National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.

Bioinformatics (Oxford, England)
|June 30, 2009
PubMed
Summary

ITM Probe models information flow in protein interaction networks using diffusion with damping. This tool identifies relevant proteins and visualizes sub-networks for hypothesis generation and confirmation.

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Protein interaction networks are crucial for understanding cellular processes.
  • Modeling information flow within these networks aids in biological discovery.
  • Existing methods may require pre-defined sub-networks of interest.

Purpose of the Study:

  • To introduce ITM Probe, a novel application for modeling information flow in protein interaction networks.
  • To provide a tool that does not require prior restriction to a specific sub-network.
  • To facilitate hypothesis formation and confirmation through network analysis.

Main Methods:

  • Utilizes a diffusion with damping approach to model information propagation.
  • Accepts user-defined origins and destinations of information.
  • Identifies and weights the most relevant proteins within the network.

Main Results:

  • ITM Probe returns a ranked list of relevant proteins.
  • A graphical representation of the corresponding sub-network is generated.
  • The resulting protein list can be directly used for enrichment analysis.

Conclusions:

  • ITM Probe effectively models information flow in protein interaction networks.
  • The application supports flexible analysis without pre-defined sub-network limitations.
  • It serves as a valuable tool for biological hypothesis generation and confirmation.