J4 ›› 2015, Vol. 14 ›› Issue (12): 39-42.

• 物理学 • 上一篇    下一篇

基于CyClus3D聚类算法的PPI网络模体研究

  

  1. (大理大学工程学院,云南大理671003)
  • 收稿日期:2015-06-24 出版日期:2015-12-15 发布日期:2015-12-15
  • 作者简介:浦恩禄,生物医学工程专业2011级本科生.
  • 基金资助:

    云南省应用基础研究计划项目(2013FD038)

Research on PPI Network Motif Based on CyClus3D Clustering Algorithm

  1. (College of Engineering, Dali University, Dali, Yunnan 671003, China)
  • Received:2015-06-24 Online:2015-12-15 Published:2015-12-15

摘要:

为了研究蛋白质间的相互作用关系,基于CyClus3D聚类算法对人类蛋白质参考数据库(HPRD)、人类相互作用组资源
(HIR)和生物相互作用数据集存储库所构成的整合型蛋白质-蛋白质相互作用网络(BioGRID)进行网络模体挖掘,然后对网络
模体所构成的子网络进行基因本体生物过程(GO)和基因组京都百科全书信号通道(KEGG)富集分析。实验结果表明:网络模
体挖掘简化了蛋白质-蛋白质相互作用网络分析,并且能够集中分析关键性的蛋白质。

关键词: 蛋白质, 蛋白质相互作用, CyClus3D聚类算法, 网络模体, 富集分析

Abstract:

To study the interactions between proteins, the 3D spectral clustering algorithm in Cytoscape(CyClus3D)is applied to
identify the network motifs of integrated protein-protein interaction(PPI)networks, including Human Protein Reference Database
(HPRD), Human Interactome Resource(HIR), and Biological General Repository for Interaction Datasets(BioGRID)databases.
Then, enrichment analysis of GO(Gene Ontology)biological process and KEGG(Kyoto Encyclopedia of Genes and Genomes)
pathways in the sub-networks formed by network motifs is conducted. The results show that network motif could simplifythe analysis of
PPI networks, and could focus on analyzing key proteins.

Key words: protein, protein-protein interaction, 3D spectral clustering algorithm, network motif, enrichment analysis

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