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A complex network analysis of hypertension-related genes

Author

Listed:
  • Wang, Huan
  • Xu, Chuan-Yun
  • Hu, Jing-Bo
  • Cao, Ke-Fei

Abstract

In this paper, a network of hypertension-related genes is constructed by analyzing the correlations of gene expression data among the Dahl salt-sensitive rat and two consomic rat strains. The numerical calculations show that this sparse and assortative network has small-world and scale-free properties. Further, 16 key hub genes (Col4a1, Lcn2, Cdk4, etc.) are determined by introducing an integrated centrality and have been confirmed by biological/medical research to play important roles in hypertension.

Suggested Citation

  • Wang, Huan & Xu, Chuan-Yun & Hu, Jing-Bo & Cao, Ke-Fei, 2014. "A complex network analysis of hypertension-related genes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 166-176.
    • Handle: RePEc:eee:phsmap:v:394:y:2014:i:c:p:166-176
    DOI: 10.1016/j.physa.2013.09.054
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    References listed on IDEAS

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    1. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 2000. "Scale-free characteristics of random networks: the topology of the world-wide web," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 281(1), pages 69-77.
    2. C. von Ferber & T. Holovatch & Yu. Holovatch & V. Palchykov, 2009. "Public transport networks: empirical analysis and modeling," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 68(2), pages 261-275, March.
    3. Tsuchiya, Masa & Selvarajoo, Kumar & Piras, Vincent & Tomita, Masaru & Giuliani, Alessandro, 2009. "Local and global responses in complex gene regulation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1738-1746.
    4. Karlsson, Fredrik & Hörnquist, Michael, 2007. "Order or chaos in Boolean gene networks depends on the mean fraction of canalizing functions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 747-757.
    5. Diambra, L., 2011. "Coarse-grain reconstruction of genetic networks from expression levels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2198-2207.
    6. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    7. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
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    Cited by:

    1. Xue-Yan Zhang & Tian-Yuan He & Chuan-Yun Xu & Ke-Fei Cao & Xu-Sheng Zhang, 2023. "Theoretical investigation of the pathway-based network of type 2 diabetes mellitus-related genes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(6), pages 1-13, June.
    2. Wang, Huan & Hu, Jing-Bo & Xu, Chuan-Yun & Zhang, De-Hai & Yan, Qian & Xu, Ming & Cao, Ke-Fei & Zhang, Xu-Sheng, 2016. "A pathway-based network analysis of hypertension-related genes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 928-939.

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