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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.
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Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
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The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
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When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze...
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Related Experiment Video

Updated: Mar 8, 2026

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
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A network-based pathway-expanding approach for pathway analysis.

Qiaosheng Zhang1,2, Jie Li3, Haozhe Xie1

  • 1School of Computer Science and Technology, Harbin Institute of Technology, West Da-Zhi Street, Harbin, China.

BMC Bioinformatics
|February 4, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a novel network-based pathway-expanding approach to identify significant biological pathways for complex diseases. The method effectively analyzes gene interactions and pathway topology, improving disease pathogenesis insights.

Keywords:
Network-basedPathway analysisProtein-protein interactionSignificant pathway

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Area of Science:

  • Systems biology
  • Computational biology
  • Genomics and proteomics

Background:

  • Pathway analysis integrating genomics and proteomics is crucial for understanding complex disease pathogenesis.
  • Existing methods often overlook interactions within and between biological pathways, presenting limitations.
  • A novel network-based approach is needed to address these challenges in pathway analysis.

Purpose of the Study:

  • To propose a network-based pathway-expanding approach that considers biological network topology.
  • To identify significant pathways involved in complex disease pathogenesis by analyzing gene interactions.
  • To overcome limitations of current pathway analysis methods.

Main Methods:

  • Construction of weighted gene-gene interaction networks (tumor and normal) using protein-protein interaction (PPI) data, gene expression, and pathway databases.
  • Identification of significant pathways by comparing topological structures of expanded pathways in weighted networks.
  • Application of the method to analyze breast cancer data and comparison with existing methods (GSEA, SPIA).

Main Results:

  • The proposed method successfully identified top pathways in breast cancer datasets, supported by biological literature.
  • The identified pathways showed significant differences in topological structures between tumor and normal networks.
  • Performance evaluation demonstrated the method's effectiveness compared to GSEA and SPIA.

Conclusions:

  • A novel network-based pathway-expanding approach effectively addresses limitations of existing pathway analysis.
  • The method accurately and reliably identifies disease-related significant pathways.
  • This approach enhances the understanding of complex disease pathogenesis through integrated network analysis.