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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,...
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-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...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...

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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

Pclust: protein network visualization highlighting experimental data.

Wenlin Li1, Lisa N Kinch, Nick V Grishin

  • 1Departments of Biophysics and Biochemistry and Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.

Bioinformatics (Oxford, England)
|August 7, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces Pclust, a web server for visualizing protein similarity networks. Pclust aids in identifying protein functions by linking clusters to experimentally characterized reference proteins and their associated data.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Proteomics

Background:

  • Inferring protein function from homologs is crucial for understanding biological systems.
  • Existing methods for analyzing protein similarity networks often lack direct links to experimentally validated data.
  • Automatic annotation transfer can introduce database errors, necessitating a focus on reliable reference proteins.

Purpose of the Study:

  • To develop a user-friendly web server, Pclust, for visualizing all-against-all pairwise similarity networks (A2ApsN).
  • To facilitate the functional interpretation of protein clusters within these networks.
  • To improve the accuracy of protein function inference by emphasizing experimentally characterized 'reference proteins'.

Main Methods:

  • Utilizing the speed of BLAST for generating all-against-all pairwise similarity networks (A2ApsN).
  • Developing a web server (Pclust) with a focus on visualizing networks and highlighting 'reference proteins'.
  • Integrating direct access to detailed information for 'reference proteins' from source databases, including PubMed.

Main Results:

  • Pclust provides a user-friendly interface for visualizing A2ApsN.
  • The server emphasizes 'reference proteins' with experimental data.
  • Cross-database linkage to sources like PubMed is readily available for 'reference proteins'.

Conclusions:

  • Pclust simplifies the identification of protein functions within similarity networks.
  • By focusing on 'reference proteins' and providing easy access to their data, Pclust aids in accurate functional deduction.
  • The tool promotes better interpretation of proteins of interest and their roles in biological pathways.