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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...
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...
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
Protein Organization01:24

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence.

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Related Experiment Video

Updated: May 29, 2026

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

A graph-based clustering method applied to protein sequences.

Pooja Mishra, Paras Nath Pandey

    Bioinformation
    |September 20, 2011
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a graph-theoretic method for clustering homologous protein sequences. The approach effectively groups similar sequences, aiding genomic analysis when structural data is limited.

    Keywords:
    Clusteringgraph-theoretic approachprotein sequences

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    An Integrated Approach for Microprotein Identification and Sequence Analysis
    09:37

    An Integrated Approach for Microprotein Identification and Sequence Analysis

    Published on: July 12, 2022

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    Last Updated: May 29, 2026

    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

    An Integrated Approach for Microprotein Identification and Sequence Analysis
    09:37

    An Integrated Approach for Microprotein Identification and Sequence Analysis

    Published on: July 12, 2022

    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • Protein sequence databases are rapidly expanding, outpacing structural determination.
    • Clustering homologous protein sequences is crucial for genomic analysis, especially with limited structural data.

    Purpose of the Study:

    • To develop an automated method for clustering homologous protein sequences using graph theory.
    • To achieve high homogeneity within clusters and strong separation between clusters.

    Main Methods:

    • Utilized graph theoretic techniques to define a similarity graph for amino acid sequences.
    • Clusters were identified as connected subgraphs within the similarity graph.
    • Applied the method to subsets of the Structural Classification of Proteins (SCOP) database.

    Main Results:

    • The number of clusters generated closely matched known superfamilies within tested SCOP subsets.
    • The method reduced the occurrence of singleton clusters.
    • Successfully grouped most remote homologous proteins.

    Conclusions:

    • Graph-theoretic clustering is an effective approach for organizing homologous protein sequences.
    • This method aids in understanding protein relationships and evolutionary patterns from sequence data alone.
    • The approach offers a valuable tool for genomic research and protein family classification.