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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,...
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Intracellular Signaling Cascades01:24

Intracellular Signaling Cascades

Once a ligand binds to a receptor, the signal is transmitted through the membrane and into the cytoplasm. The continuation of a signal in this manner is called signal transduction. Signal transduction only occurs with cell-surface receptors, which cannot interact with most components of the cell, such as DNA. Only internal receptors can interact directly with DNA in the nucleus to initiate protein synthesis. When a ligand binds to its receptor, conformational changes occur that affect the...
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...

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

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CASCADE: a novel quasi all paths-based network analysis algorithm for clustering biological interactions.

Woochang Hwang1, Young-Rae Cho, Aidong Zhang

  • 1Department of Computer Science and Engineering, State University of New York, Buffalo, NY 14260, USA. whwang2@cse.buffalo.edu

BMC Bioinformatics
|January 31, 2008
PubMed
Summary
This summary is machine-generated.

We developed CASCADE, a novel method for analyzing protein-protein interaction (PPI) networks. CASCADE effectively identifies biologically relevant functional modules within PPI networks with improved accuracy and reduced data loss.

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Area of Science:

  • Computational Biology
  • Network Science
  • Systems Biology

Background:

  • Protein-protein interaction (PPI) networks are crucial for understanding biological functions.
  • Quantitative analysis of PPI network topology aids in identifying functional modules.
  • Existing methods for PPI network clustering have limitations in accuracy and data retention.

Purpose of the Study:

  • To introduce a novel clustering methodology for PPI networks.
  • To model the biological and topological influence of proteins using an "occurrence probability."
  • To improve the detection of biologically relevant functional modules in PPI networks.

Main Methods:

  • Developed CASCADE, a clustering methodology for PPI networks.
  • Modeled protein influence using the probability distribution of interaction occurrences over time.
  • Iteratively refined clusters based on occurrence probability and graph topology.

Main Results:

  • CASCADE identified larger clusters with significantly improved biological function enrichment (p-values ~1000-fold better than competing methods).
  • The CASCADE approach demonstrated a substantially lower protein discard rate compared to other methods (average 45% discard rate for others).
  • CASCADE outperformed nine competing approaches on the yeast PPI network dataset.

Conclusions:

  • CASCADE is an effective tool for detecting biologically relevant clusters in PPI networks.
  • The method offers enhanced accuracy and efficiency in identifying functional modules.
  • CASCADE provides a more comprehensive analysis by minimizing data loss.