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Organizational structure and the periphery of the gene regulatory network in B-cell lymphoma.

  • Ricardo de Matos Simoes
  • , Shailesh Tripathi
  • , Frank Emmert-Streib*
  • *Tämän työn vastaava kirjoittaja

    Tutkimustuotos: ArtikkeliTieteellinenvertaisarvioitu

    20 Sitaatiot (Scopus)

    Abstrakti

    The physical periphery of a biological cell is mainly described by signaling pathways which are triggered by transmembrane proteins and receptors that are sentinels to control the whole gene regulatory network of a cell. However, our current knowledge about the gene regulatory mechanisms that are governed by extracellular signals is severely limited. The purpose of this paper is three fold. First, we infer a gene regulatory network from a large-scale B-cell lymphoma expression data set using the C3NET algorithm. Second, we provide a functional and structural analysis of the largest connected component of this network, revealing that this network component corresponds to the peripheral region of a cell. Third, we analyze the hierarchical organization of network components of the whole inferred B-cell gene regulatory network by introducing a new approach which exploits the variability within the data as well as the inferential characteristics of C3NET. As a result, we find a functional bisection of the network corresponding to different cellular components. Overall, our study allows to highlight the peripheral gene regulatory network of B-cells and shows that it is centered around hub transmembrane proteins located at the physical periphery of the cell. In addition, we identify a variety of novel pathological transmembrane proteins such as ion channel complexes and signaling receptors in B-cell lymphoma.

    AlkuperäiskieliEnglanti
    Artikkeli38
    JulkaisuBMC Systems Biology
    Vuosikerta6
    DOI - pysyväislinkit
    TilaJulkaistu - 14 toukok. 2012
    OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

    !!ASJC Scopus subject areas

    • Molecular Biology
    • Structural Biology
    • Applied Mathematics
    • Modelling and Simulation
    • Computer Science Applications

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