About this Journal Submit a Manuscript Table of Contents
Journal of Biomedicine and Biotechnology
Volume 2011 (2011), Article ID 926407, 7 pages
http://dx.doi.org/10.1155/2011/926407
Research Article

Inequalities and Duality in Gene Coexpression Networks of HIV-1 Infection Revealed by the Combination of the Double-Connectivity Approach and the Gini's Method

1Saban Research Institute of Childrens Hospital Los Angeles, Department of Pediatrics, University of Southern California, Los Angeles, CA 90027, USA
2Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China

Received 21 May 2011; Accepted 13 July 2011

Academic Editor: Decheng Yang

Copyright © 2011 Chuang Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Ray and W. Zhang, “Analysis of Alzheimer's disease severity across brain regions by topological analysis of gene co-expression networks,” BMC Systems Biology, vol. 4, 136, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. J. A. Miller, S. Horvath, and D. H. Geschwind, “Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways,” Proceedings of the National Academy of Sciences of the United States of America, vol. 107, no. 28, pp. 12698–12703, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. F. E. Dewey, M. V. Perez, M. T. Wheeler et al., “Gene coexpression network topology of cardiac development, hypertrophy, and failure,” Circulation, vol. 4, no. 1, pp. 26–35, 2011. View at Publisher · View at Google Scholar
  4. A. J. Walley, P. Jacobson, M. Falchi, et al., “Differential coexpression analysis of obesity-associated networks in human subcutaneous adipose tissue,” International Journal of Obesity. In press. View at Publisher · View at Google Scholar
  5. A. Torkamani, B. Dean, N. J. Schork, and E. A. Thomas, “Coexpression network analysis of neural tissue reveals perturbations in developmental processes in schizophrenia,” Genome Research, vol. 20, no. 4, pp. 403–412, 2010. View at Publisher · View at Google Scholar · View at Scopus
  6. M. P. Gustin, C. Z. Paultre, J. Random, G. Bricca, and C. Cerutti, “Functional meta-analysis of double connectivity in gene coexpression networks in mammals,” Physiological Genomics, vol. 34, no. 1, pp. 34–41, 2008. View at Publisher · View at Google Scholar · View at Scopus
  7. L. Mao, J. L. van Hemert, S. Dash, and J. A. Dickerson, “Arabidopsis gene co-expression network and its functional modules,” BMC Bioinformatics, vol. 10, article 346, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. S. Horvath and J. Dong, “Geometric interpretation of gene coexpression network analysis,” PLoS Computational Biology, vol. 4, no. 8, Article ID e1000117, 2008. View at Publisher · View at Google Scholar · View at Scopus
  9. A. E. Teschendorff and S. Severini, “Increased entropy of signal transduction in the cancer metastasis phenotype,” BMC Systems Biology, vol. 4, article 104, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. R. R. Nayak, M. Kearns, R. S. Spielman, and V. G. Cheung, “Coexpression network based on natural variation in human gene expression reveals gene interactions and functions,” Genome Research, vol. 19, no. 11, pp. 1953–1962, 2009. View at Publisher · View at Google Scholar · View at Scopus
  11. J. K. Choi, U. Yu, O. J. Yoo, and S. Kim, “Differential coexpression analysis using microarray data and its application to human cancer,” Bioinformatics, vol. 21, no. 24, pp. 4348–4355, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. S. G. Ma, M. Y. Shi, Y. Li, D. H. Yi, and B. C. Shia, “Incorportating gene co-expression network in identification of cancer prognosis markers,” BMC Bioinformatics, vol. 11, article 271, 2010. View at Publisher · View at Google Scholar
  13. S. H. Huang, W. Zhou, and A. Jong, “Focal point theory models for dissecting dynamic duality problems of microbial infections,” Journal of Biomedicine and Biotechnology, vol. 2008, no. 1, Article ID 856314, 8 pages, 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. S. Moir, T. W. Chun, and A. S. Fauci, “Pathogenic mechanisms of HIV disease,” Annual Review of Pathology, vol. 6, pp. 223–248, 2011. View at Publisher · View at Google Scholar
  15. M. Permanyer, E. Ballana, and J. A. Este, “Endocytosis of HIV: anything goes,” Trends in Microbiology, vol. 18, no. 12, pp. 543–551, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. J. Fellay, K. V. Shianna, A. Telenti, and D. B. Goldstein, “Host genetics and HIV-1: the final phase?” PLoS Pathogens, vol. 6, no. 10, Article ID e1001033, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. Q. Li, A. J. Smith, T. W. Schacker et al., “Microarray analysis of lymphatic tissue reveals stage-specific, gene expression signatures in HIV-1 infection,” Journal of Immunology, vol. 183, no. 3, pp. 1975–1982, 2009. View at Publisher · View at Google Scholar · View at Scopus
  18. N. Kondo, G. Sembajwe, I. Kawachi, R. M. van Dam, S. V. Subramanian, and Z. Yamagata, “Income inequality, mortality, and self rated health: meta-analysis of multilevel studies,” British Medical Journal, vol. 339, Article ID b4471, 2009. View at Publisher · View at Google Scholar · View at Scopus
  19. A. L. Jackson, C. A. Davies, and A. H. Leyland, “Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?” BMC Medical Research Methodology, vol. 10, article 74, 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. M. A. Munga and O. Mæstad, “Measuring inequalities in the distribution of health workers: the case of Tanzania,” Human Resources for Health, vol. 7, article 4, 2009. View at Publisher · View at Google Scholar · View at Scopus
  21. G. J. Glasser, “Variance formulas for the mean difference and coefficient of concentration,” Journal of the American Statistical Association, vol. 57, no. 299, pp. 648–654, 1962.
  22. E. Schechtman and S. Yitzhaki, “On the proper bounds of the Gini correlation,” Economics Letters, vol. 63, no. 2, pp. 133–138, 1999. View at Scopus
  23. W. C. Xu, Y. S. Hung, M. Niranjan, and M. F. Shen, “Asymptotic mean and variance of Gini correlation for bivariate normal samples,” IEEE Transactions on Signal Processing, vol. 58, no. 2, pp. 522–534, 2010. View at Publisher · View at Google Scholar · View at Scopus
  24. K. N. Aldy, N. C. Horton, P. A. Mathew, and S. O. Mathew, “2B4+ CD8+ T cells play an inhibitory role against constrained HIV epitopes,” Biochemical and Biophysical Research Communications, vol. 405, no. 3, pp. 503–507, 2011. View at Publisher · View at Google Scholar
  25. Y. H. Zheng, H. F. Yu, and B. M. Peterlin, “Human p32 protein relieves a post-transcriptional block to HIV replication in murine cells,” Nature Cell Biology, vol. 5, no. 7, pp. 611–618, 2003. View at Publisher · View at Google Scholar · View at Scopus
  26. N. K. Saksena, B. Rodes, B. Wang, and V. Soriano, “Elite HIV controllers: myth or reality?” AIDS Reviews, vol. 9, no. 4, pp. 195–207, 2007. View at Scopus
  27. G. Silvestri, M. Paiardini, I. Pandrea, M. M. Lederman, and D. L. Sodora, “Understanding the benign nature of SIV infection in natural hosts,” Journal of Clinical Investigation, vol. 117, no. 11, pp. 3148–3154, 2007. View at Publisher · View at Google Scholar · View at Scopus
  28. L. Weiss, C. Piketty, L. Assoumou et al., “Relationship between regulatory T cells and immune activation in human immunodeficiency virus-infected patients interrupting antiretroviral therapy,” PLoS ONE, vol. 5, no. 7, Article ID e11659, 2010. View at Publisher · View at Google Scholar · View at Scopus
  29. P. Ancuta, P. Monteiro, and R. P. Sekaly, “Th17 lineage commitment and HIV-1 pathogenesis,” Current Opinion in HIV and AIDS, vol. 5, no. 2, pp. 158–165, 2010. View at Publisher · View at Google Scholar · View at Scopus
  30. M. Natarajan, A. August, and A. J. Henderson, “Combinatorial signals from CD28 differentially regulate human immunodeficiency virus transcription in T cells,” Journal of Biological Chemistry, vol. 285, no. 23, pp. 17338–17347, 2010. View at Publisher · View at Google Scholar · View at Scopus
  31. V. Giordanengo, M. Limouse, A. Doglio, J. Lesimple, and J. C. Lefebvre, “Alteration of CD44 expression in HIV type 1-infected T cell lines,” AIDS Research and Human Retroviruses, vol. 12, no. 17, pp. 1615–1622, 1996. View at Scopus
  32. J. S. Albin, R. S. LaRue, J. A. Weaver et al., “A single amino acid in human APOBEC3F alters susceptibility to HIV-1 Vif,” Journal of Biological Chemistry, vol. 285, no. 52, pp. 40785–40792, 2010. View at Publisher · View at Google Scholar · View at Scopus
  33. A. Okumura, G. Lu, I. P. Rowe, and P. M. Pitha, “Innate antiviral response targets HIV-1 release by the induction of ubiquitin-like protein ISG15,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 5, pp. 1440–1445, 2006. View at Publisher · View at Google Scholar · View at Scopus