• DocumentCode
    680163
  • Title

    Yin and Yang of reciprocally scale-free biological networks between disease genes and death genes

  • Author

    Ju Han Kim

  • Author_Institution
    Seoul Nat. Univ., Seoul, South Korea
  • fYear
    2013
  • fDate
    18-21 Dec. 2013
  • Firstpage
    2
  • Lastpage
    2
  • Abstract
    Summary form only given. Biological networks often show a scale-free power-law distribution. Furthermore, leathal genes tend to form functional hubs whereas non-leathal disease genes are located at the periphery. Uni-dimensional analyses, however, are flawed. Here we report two distinct scale-free networks; a protein-protein interaction (PPI) and a perturbation-sensitivity (PSN) network. Hubs of both networks demonstrate a low molecular evolutionary rate and a high codon adaptation index, indicating that both hubs have been shaped under high evolutionary selective pressure. Moreover, the topologies of PPI and PSN are inversely proportional: hubs of PPI tend to be located at the periphery of PSN and vice versa. PPI hubs are highly enriched with lethal genes whereas PSN hubs with disease genes and drug targets. PPI network hubs are enriched with essential cellular processes whereas PSN hubs with environmental interactions like TATA boxes and transcription factor binding sites. It is concluded that biological systems may balance internal growth signaling and external stress signaling by unifying the two opposite scale-free networks that are reciprocal to each other but work in concert between death and disease.
  • Keywords
    bioinformatics; cellular biophysics; diseases; drugs; evolution (biological); genetics; genomics; molecular biophysics; proteins; PPI network hubs; PPI topologies; PSN topologies; TATA boxes; biological networks; biological systems; cellular processes; codon adaptation index; death genes; drug targets; environmental interactions; external stress signaling; internal growth signaling; molecular evolutionary rate; nonleathal disease genes; perturbation-sensitivity network; protein-protein interaction networks; scale-free power-law distribution; transcription factor binding sites; unidimensional analyses;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
  • Conference_Location
    Shanghai
  • Type

    conf

  • DOI
    10.1109/BIBM.2013.6732449
  • Filename
    6732449