Computational Systems Biology Methods and Protocols.7z

(nextflipdebug5) #1
and subtype features by molecular data inte-
gration. Bioinformatics 32(17):i445–i454.
https://doi.org/10.1093/bioinformatics/
btw434


  1. Seely JS, Kaufman MT, Ryu SI, Shenoy KV,
    Cunningham JP, Churchland MM (2016)
    Tensor analysis reveals distinct population
    structure that parallels the different computa-
    tional roles of areas M1 and V1. PLoS Com-
    put Biol 12(11):e1005164.https://doi.org/
    10.1371/journal.pcbi.1005164

  2. Hore V, Vinuela A, Buil A, Knight J,
    McCarthy MI, Small K, Marchini J (2016)
    Tensor decomposition for multiple-tissue
    gene expression experiments. Nat Genet 48
    (9):1094–1100. https://doi.org/10.1038/
    ng.3624

  3. Bersanelli M, Mosca E, Remondini D,
    Giampieri E, Sala C, Castellani G, Milanesi L
    (2016) Methods for the integration of multi-
    omics data: mathematical aspects. BMC Bio-
    informatics 17(Suppl 2):15.https://doi.org/
    10.1186/s12859-015-0857-9

  4. Meng C, Zeleznik OA, Thallinger GG,
    Kuster B, Gholami AM, Culhane AC (2016)
    Dimension reduction techniques for the inte-
    grative analysis of multi-omics data. Brief
    Bioinform 17(4):628–641.https://doi.org/
    10.1093/bib/bbv108

  5. Luo Y, Wang F, Szolovits P (2016) Tensor
    factorization toward precision medicine.
    Brief Bioinform.https://doi.org/10.1093/
    bib/bbw026

  6. Vargas AJ, Harris CC (2016) Biomarker
    development in the precision medicine era:
    lung cancer as a case study. Nat Rev Cancer
    16(8):525–537. https://doi.org/10.1038/
    nrc.2016.56

  7. Lahti L, Schafer M, Klein HU, Bicciato S,
    Dugas M (2013) Cancer gene prioritization
    by integrative analysis of mRNA expression
    and DNA copy number data: a comparative
    review. Brief Bioinform 14(1):27–35.
    https://doi.org/10.1093/bib/bbs005

  8. Genomes Project C, Abecasis GR, Auton A,
    Brooks LD, DePristo MA, Durbin RM,
    Handsaker RE, Kang HM, Marth GT,
    McVean GA (2012) An integrated map of
    genetic variation from 1,092 human gen-
    omes. Nature 491(7422):56–65. https://
    doi.org/10.1038/nature11632

  9. Gerstein M (2012) Genomics: ENCODE
    leads the way on big data. Nature 489
    (7415):208. https://doi.org/10.1038/
    489208b

  10. Nagano T, Lubling Y, Stevens TJ,
    Schoenfelder S, Yaffe E, Dean W, Laue ED,


Tanay A, Fraser P (2013) Single-cell Hi-C
reveals cell-to-cell variability in chromosome
structure. Nature 502(7469):59–64.https://
doi.org/10.1038/nature12593


  1. Dekker J, Marti-Renom MA, Mirny LA
    (2013) Exploring the three-dimensional
    organization of genomes: interpreting chro-
    matin interaction data. Nat Rev Genet 14
    (6):390–403. https://doi.org/10.1038/
    nrg3454

  2. Yun X, Xia L, Tang B, Zhang H, Li F, Zhang
    Z (2016) 3CDB: a manually curated database
    of chromosome conformation capture data.
    Database (Oxford). https://doi.org/10.
    1093/database/baw044

  3. Teng L, He B, Wang J, Tan K (2016) 4DGe-
    nome: a comprehensive database of chroma-
    tin interactions. Bioinformatics 32(17):2727.
    https://doi.org/10.1093/bioinformatics/
    btw375

  4. Barrett T, Wilhite SE, Ledoux P,
    Evangelista C, Kim IF, Tomashevsky M, Mar-
    shall KA, Phillippy KH, Sherman PM,
    Holko M, Yefanov A, Lee H, Zhang N,
    Robertson CL, Serova N, Davis S, Soboleva
    A (2013) NCBI GEO: archive for functional
    genomics data sets--update. Nucleic Acids
    Res 41(Database issue):D991–D995.
    https://doi.org/10.1093/nar/gks1193

  5. Kim HS, Minna JD, White MA (2013) GWAS
    meets TCGA to illuminate mechanisms of
    cancer predisposition. Cell 152(3):387–389.
    https://doi.org/10.1016/j.cell.2013.01.
    027

  6. International Cancer Genome C, Hudson TJ,
    Anderson W, Artez A, Barker AD, Bell C,
    Bernabe RR, Bhan MK, Calvo F, Eerola I,
    Gerhard DS, Guttmacher A, Guyer M, Hems-
    ley FM, Jennings JL, Kerr D, Klatt P, Kolar P,
    Kusada J, Lane DP, Laplace F, Youyong L,
    Nettekoven G, Ozenberger B, Peterson J,
    Rao TS, Remacle J, Schafer AJ, Shibata T,
    Stratton MR, Vockley JG, Watanabe K,
    Yang H, Yuen MM, Knoppers BM,
    Bobrow M, Cambon-Thomsen A, Dressler
    LG, Dyke SO, Joly Y, Kato K, Kennedy KL,
    Nicolas P, Parker MJ, Rial-Sebbag E, Romeo-
    Casabona CM, Shaw KM, Wallace S, Wiesner
    GL, Zeps N, Lichter P, Biankin AV,
    Chabannon C, Chin L, Clement B, de
    Alava E, Degos F, Ferguson ML, Geary P,
    Hayes DN, Hudson TJ, Johns AL,
    Kasprzyk A, Nakagawa H, Penny R, Piris
    MA, Sarin R, Scarpa A, Shibata T, van de
    Vijver M, Futreal PA, Aburatani H, Bayes M,
    Botwell DD, Campbell PJ, Estivill X, Gerhard
    DS, Grimmond SM, Gut I, Hirst M, Lopez-
    Otin C, Majumder P, Marra M, McPherson


Integrative Analysis of Omics Big Data 129
Free download pdf