메뉴 건너뛰기




Volumn 10, Issue 1, 2011, Pages

Sparse canonical covariance analysis for high-throughput data

Author keywords

canonical covariance analysis; high dimensional genomic data; random effect model; sparsity

Indexed keywords

ANALYSIS OF COVARIANCE; DATA ANALYSIS; GENE EXPRESSION; HUMAN; HUMAN CELL; INTERMETHOD COMPARISON; MATHEMATICAL MODEL; MATHEMATICAL VARIABLE; NEOPLASM; NONLINEAR ITERATIVE PARTIAL LEAST SQUARE; PARTIAL LEAST SQUARES REGRESSION; PERFORMANCE; PROTEIN EXPRESSION; REVIEW; SIMULATION; SPARSE CANONICAL COVARIANCE ANALYSIS; TECHNIQUE;

EID: 79961234299     PISSN: None     EISSN: 15446115     Source Type: Journal    
DOI: 10.2202/1544-6115.1638     Document Type: Review
Times cited : (26)

References (26)
  • 1
    • 74049093630 scopus 로고    scopus 로고
    • Sparse partial least squares regression for simulta-neous dimension reduction and variable selection
    • Chun, H. and Keles, S. (2010): Sparse partial least squares regression for simulta-neous dimension reduction and variable selection. Journal of Royal Statistical Society, Series B. 72, 3-25.
    • (2010) Journal of Royal Statistical Society, Series B , vol.72 , pp. 3-25
    • Chun, H.1    Keles, S.2
  • 3
    • 0001038826 scopus 로고
    • Covariance selection
    • Demster, A.P. (1972): Covariance selection. Biometrics 28, 157-175.
    • (1972) Biometrics , vol.28 , pp. 157-175
    • Demster, A.P.1
  • 4
    • 1542784498 scopus 로고    scopus 로고
    • Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
    • Fan, J. and Li, R. (2001): Variable selection via nonconcave penalized likelihood and its oracle properties. Journal of American Statistical Association. 96, 1348-1360. (Pubitemid 33695585)
    • (2001) Journal of the American Statistical Association , vol.96 , Issue.456 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 6
    • 0004151494 scopus 로고
    • Cambridge: Cambridge univer-sity press
    • Horn, R. and Johnson, C.(1985): Matrix analysis. Cambridge: Cambridge univer-sity press.
    • (1985) Matrix Analysis
    • Horn, R.1    Johnson, C.2
  • 8
    • 26444617168 scopus 로고    scopus 로고
    • Variable selection using MM algorithms
    • DOI 10.1214/009053605000000200
    • Hunter, D.R. and Li, R. (2005): Variable selection using MM algorithms. Annals of Statistics. 33, 1617-1642. (Pubitemid 41423982)
    • (2005) Annals of Statistics , vol.33 , Issue.4 , pp. 1617-1642
    • Hunter, D.R.1    Li, R.2
  • 9
    • 66549088006 scopus 로고    scopus 로고
    • On consistency and sparsity for principal compo-nents analysis in high dimensions
    • Johnstone, I. and Lu, A. (2009): On consistency and sparsity for principal compo-nents analysis in high dimensions. Journal of American Statistical Association. 104, 682-693.
    • (2009) Journal of American Statistical Association , vol.104 , pp. 682-693
    • Johnstone, I.1    Lu, A.2
  • 10
    • 0000020007 scopus 로고
    • Canonical analysis of several sets of variables
    • Kettenring, J.R. (1971): Canonical analysis of several sets of variables. Biometrika. 58, 433-451.
    • (1971) Biometrika , vol.58 , pp. 433-451
    • Kettenring, J.R.1
  • 11
    • 60849113429 scopus 로고    scopus 로고
    • Sparse canonical methods for biological data integration: Application to a cross platform study
    • Le Cao, K.A., Martin, P.G. Robert-Granie, C. and Besse, P. (2009): Sparse canonical methods for biological data integration: Application to a cross platform study. BMC Bioinformatics 10, 10-34.
    • (2009) BMC Bioinformatics , vol.10 , pp. 10-34
    • Le Cao, K.A.1    Martin, P.G.2    Robert-Granie, C.3    Besse, P.4
  • 12
    • 77954586272 scopus 로고    scopus 로고
    • Super sparse principal compo-nent analysis for high-throughput genomic data
    • doi:10.1186/1471-2105-11-296
    • Lee, D., Lee, W., Lee, Y. and Pawitan, Y. (2010): Super sparse principal compo-nent analysis for high-throughput genomic data. BMC Bioinformatics 11:296 doi:10.1186/1471-2105-11-296.
    • (2010) BMC Bioinformatics , vol.11 , pp. 296
    • Lee, D.1    Lee, W.2    Lee, Y.3    Pawitan, Y.4
  • 15
    • 79961217712 scopus 로고    scopus 로고
    • Technical report No.2009-4, Department of Statistics, Stanford university
    • Lee, Y. and Oh, H. (2009): Random effect models for variable selection. Technical report No.2009-4, Department of Statistics, Stanford university.
    • (2009) Random Effect Models for Variable Selection
    • Lee, Y.1    Oh, H.2
  • 18
    • 34249029861 scopus 로고    scopus 로고
    • Penalized model-based clustering with application to variable selection
    • Pan, W. and Shen, X. (2007): Penalized model-based clustering with application to variable selection. Journal of Machine Learning Research 8, 1145-1164. (Pubitemid 46798406)
    • (2007) Journal of Machine Learning Research , vol.8 , pp. 1145-1164
    • Pan, W.1    Shen, X.2
  • 20
    • 38049082898 scopus 로고    scopus 로고
    • Genome-wide spare canon-ical correlation of gene expression with genotypes
    • Parkomenko, E., Tritchler, D. and Beyene, J. (2007): Genome-wide spare canon-ical correlation of gene expression with genotypes. BMC Proceedings 1(suppl 1):S119.
    • (2007) BMC Proceedings , vol.1 , Issue.SUPPL. 1
    • Parkomenko, E.1    Tritchler, D.2    Beyene, J.3
  • 24
    • 18444418008 scopus 로고    scopus 로고
    • Modelling association between two irregularly observed spatiotemporal processes by using maximum covariance analysis
    • DOI 10.1111/j.1467-9876.2005.05300.x
    • Salim, A., Pawitan, Y. and Bond, K. (2005): Modelling association between two irregularly observed spatiotemporal processes by using maximum covariance analysis. Applied Statistics. 54, 555-573. (Pubitemid 40653847)
    • (2005) Journal of the Royal Statistical Society. Series C: Applied Statistics , vol.54 , Issue.3 , pp. 555-573
    • Salim, A.1    Pawitan, Y.2    Bond, K.3
  • 26
    • 70350276186 scopus 로고    scopus 로고
    • Correlating gene and protein expression data using Correlated Factor Analysis
    • doi:10.1186/1471-2105-10-272
    • Tan, C.S., Salim, A., Ploner, A., Lehtio, J., Chia, K.S. and Pawitan, Y. (2009): Correlating gene and protein expression data using Correlated Factor Analysis. BMC Bioinformatics. 10:272 doi:10.1186/1471-2105-10-272.
    • (2009) BMC Bioinformatics , vol.10 , pp. 272
    • Tan, C.S.1    Salim, A.2    Ploner, A.3    Lehtio, J.4    Chia, K.S.5    Pawitan, Y.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.