Computational Systems Biology Methods and Protocols.7z

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to human T helper cell differentiation process.
Bioinformatics 23(16):2096–2103


  1. Jiang X, Zhang H, Quan X (2016) Differen-
    tially Coexpressed disease gene identification
    based on gene Coexpression network. Biomed
    Res Int 2016:3962761

  2. Yang J et al (2013) DCGL v2.0: an R package
    for unveiling differential regulation from differ-
    ential co-expression. PLoS One 8(11):e79729

  3. Watson M (2006) CoXpress: differential
    co-expression in gene expression data. BMC
    Bioinformatics 7:509

  4. Tesson BM, Breitling R, Jansen RC (2010)
    DiffCoEx: a simple and sensitive method to
    find differentially coexpressed gene modules.
    BMC Bioinformatics 11:497

  5. Choi Y, Kendziorski C (2009) Statistical meth-
    ods for gene set co-expression analysis. Bioin-
    formatics 25(21):2780–2786

  6. Rahmatallah Y, Emmert-Streib F, Glazko G
    (2014) Gene sets net correlations analysis
    (GSNCA): a multivariate differential coexpres-
    sion test for gene sets. Bioinformatics 30
    (3):360–368

  7. Amar D, Safer H, Shamir R (2013) Dissection
    of regulatory networks that are altered in dis-
    ease via differential co-expression. PLoS Com-
    put Biol 9(3):e1002955

  8. Lai Y et al (2004) A statistical method for iden-
    tifying differential gene-gene co-expression
    patterns. Bioinformatics 20(17):3146–3155

  9. Choi JK et al (2005) Differential coexpression
    analysis using microarray data and its applica-
    tion to human cancer. Bioinformatics 21
    (24):4348–4355

  10. Yoon SH, Kim JS, Song HH (2003) Statistical
    inference methods for detecting altered gene
    associations. Genome Inform 14:54–63

  11. Li KC (2002) Genome-wide coexpression
    dynamics: theory and application. Proc Natl
    Acad Sci USA 99(26):16875–16880

  12. McKenzie AT et al (2016) DGCA: a compre-
    hensive R package for differential gene correla-
    tion analysis. BMC Syst Biol 10(1):106

  13. Fukushima A (2013) DiffCorr: an R package to
    analyze and visualize differential correlations in
    biological networks. Gene 518(1):209–214
    28. Dawson JA, Ye S, Kendziorski C (2012)
    R/EBcoexpress: an empirical Bayesian frame-
    work for discovering differential co-expression.
    Bioinformatics 28(14):1939–1940
    29. Siska C, Bowler R, Kechris K (2016) The
    discordant method: a novel approach for dif-
    ferential correlation. Bioinformatics 32
    (5):690–696
    30. Deng SP, Zhu L, Huang DS (2015) Mining
    the bladder cancer-associated genes by an
    integrated strategy for the construction and
    analysis of differential co-expression networks.
    BMC Genomics 16(Suppl 3):S4
    31. Jia X et al (2014) Cancer-risk module identifi-
    cation and module-based disease risk evalua-
    tion: a case study on lung cancer. PLoS One 9
    (3):e92395
    32. Hong S et al (2011) Gene co-expression net-
    work and functional module analysis of ovarian
    cancer. Int J Comput Biol Drug Des 4
    (2):147–164
    33. Ivliev AE et al (2016) Drug repositioning
    through systematic Mining of Gene Coexpres-
    sion Networks in cancer. PLoS One 11(11):
    e0165059
    34. Giulietti M et al (2016) Weighted gene
    co-expression network analysis reveals key
    genes involved in pancreatic ductal adenocarci-
    noma development. Cell Oncol (Dordr) 39
    (4):379–388
    35. Gu Y et al (2017) Identification of prognostic
    genes in kidney renal clear cell carcinoma by
    RNAseq data analysis. Mol Med Rep 15
    (4):1661–1667
    36. Oros Klein K et al (2016) Gene Coexpression
    analyses differentiate networks associated with
    diverse cancers Harboring TP53 missense or
    null mutations. Front Genet 7:137
    37. Li C et al (2013) Gene expression patterns
    combined with bioinformatics analysis identify
    genes associated with cholangiocarcinoma.
    Comput Biol Chem 47:192–197
    38. Cao MS et al (2015) Differential network anal-
    ysis reveals dysfunctional regulatory networks
    in gastric carcinogenesis. Am J Cancer Res 5
    (9):2605–2625


Differential Coexpression Network Analysis for Gene Expression Data 165
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