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

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• 作者：Ricardo de Matos Simoes (1)
  Shailesh Tripathi (1)
  Frank Emmert-Streib (1)
  
• 关键词：B ; cell lymphoma ; Gene expression data ; Gene regulatory network ; Statistical network inference
• 刊名：BMC Systems Biology
• 出版年：2012
• 出版时间：December 2012
• 年：2012
• 卷：6
• 期：1
• 全文大小：2118KB
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• 作者单位：Ricardo de Matos Simoes (1)
  Shailesh Tripathi (1)
  Frank Emmert-Streib (1)
  
  1. Computational Biology and Machine Learning Lab, Center for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Queen鈥檚 University Belfast, Belfast, UK
  

文摘

Background 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. Results 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. Conclusions 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.