Analysis of Protein–Protein Functional Associations by Using Gene Ontology and KEGG Pathway.

Protein–protein interaction (PPI) plays an extremely remarkable role in the growth, reproduction, and metabolism of all lives. A thorough investigation of PPI can uncover the mechanism of how proteins express their functions. In this study, we used gene ontology (GO) terms and biological pathways to...

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Publicado en:BioMed Research International pp. 1 - 11
Autores principales: Yuan, Fei, Pan, Xiaoyong, Chen, Lei, Zhang, Yu-Hang, Huang, Tao, Cai, Yu-Dong
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 7/18/2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 7/18/2019
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2019/4963289
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        atl: Analysis of Protein–Protein Functional Associations by Using Gene Ontology and KEGG Pathway.
      aug:
        au:
          Yuan, Fei
          Pan, Xiaoyong
          Chen, Lei
          Zhang, Yu-Hang
          Huang, Tao
          Cai, Yu-Dong
        affil: Department of Science & Technology, Binzhou Medical University Hospital, Binzhou 256603, Shandong, China
      sug:
        subj:
          Proteins Analysis
          Signal Transduction
          Genetic Techniques
          Biochemical Phenomena
          Ontologies
          Human
          Gene Expression Profiling
      ab: Protein–protein interaction (PPI) plays an extremely remarkable role in the growth, reproduction, and metabolism of all lives. A thorough investigation of PPI can uncover the mechanism of how proteins express their functions. In this study, we used gene ontology (GO) terms and biological pathways to study an extended version of PPI (protein–protein functional associations) and subsequently identify some essential GO terms and pathways that can indicate the difference between two proteins with and without functional associations. The protein–protein functional associations validated by experiments were retrieved from STRING, a well-known database on collected associations between proteins from multiple sources, and they were termed as positive samples. The negative samples were constructed by randomly pairing two proteins. Each sample was represented by several features based on GO and KEGG pathway information of two proteins. Then, the mutual information was adopted to evaluate the importance of all features and some important ones could be accessed, from which a number of essential GO terms or KEGG pathways were identified. The final analysis of some important GO terms and one KEGG pathway can partly uncover the difference between proteins with and without functional associations.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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