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Volumn 69, Issue 3, 2013, Pages 582-593

Network-Based Penalized Regression With Application to Genomic Data

Author keywords

Gene expression; Networks analysis; Nonconvex minimization; Penalty; Truncated Lasso penalty

Indexed keywords

CLUSTERING ALGORITHMS; CONVEX OPTIMIZATION; REGRESSION ANALYSIS;

EID: 84901243203     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/biom.12035     Document Type: Article
Times cited : (39)

References (28)
  • 3
    • 39849102639 scopus 로고    scopus 로고
    • Simultaneous regression shrinkage, feature selection and supervised clustering of predictors with OSCAR
    • Bondell, H. D. and Reich, B. J. (2008). Simultaneous regression shrinkage, feature selection and supervised clustering of predictors with OSCAR. Biometrics 64, 115-123.
    • (2008) Biometrics , vol.64 , pp. 115-123
    • Bondell, H.D.1    Reich, B.J.2
  • 6
    • 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 the American Statistical Association 96, 1348-1360.
    • (2001) Journal of the American Statistical Association , vol.96 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 7
    • 51349098876 scopus 로고    scopus 로고
    • CVX: Matlab software for disciplined convex programming, version 1.21
    • Grant, M. and Boyd, S. (2011). CVX: Matlab software for disciplined convex programming, version 1.21 http://cvxr.com/cvx
    • (2011)
    • Grant, M.1    Boyd, S.2
  • 8
    • 84862830750 scopus 로고    scopus 로고
    • Network based prediction model for genomic data analysis
    • Huang, Y. and Wang, P. (2012) Network based prediction model for genomic data analysis. Statistics in Biosciences 4, 47-65.
    • (2012) Statistics in Biosciences , vol.4 , pp. 47-65
    • Huang, Y.1    Wang, P.2
  • 9
    • 0033982936 scopus 로고    scopus 로고
    • KEGG: Kyoto encyclopedia of genes and genomes
    • Kanehisa, M. and Goto, S. (2000). KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28, 27-30.
    • (2000) Nucleic Acids Res , vol.28 , pp. 27-30
    • Kanehisa, M.1    Goto, S.2
  • 10
    • 42649140560 scopus 로고    scopus 로고
    • Network-constrained regularization and variable selection for analysis of genomic data
    • Li, C. and Li, H. (2008). Network-constrained regularization and variable selection for analysis of genomic data. Bioinformatics 24, 1175-1118.
    • (2008) Bioinformatics , vol.24 , pp. 1118-1175
    • Li, C.1    Li, H.2
  • 11
    • 80052861336 scopus 로고    scopus 로고
    • Variable selection and regression analysis for graph-structured covariates with an application to genomics
    • Li, C. and Li, H. (2010). Variable selection and regression analysis for graph-structured covariates with an application to genomics. Annals of Applied Statistics 4, 1498-1516.
    • (2010) Annals of Applied Statistics , vol.4 , pp. 1498-1516
    • Li, C.1    Li, H.2
  • 12
    • 78649419087 scopus 로고    scopus 로고
    • Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics
    • Li, F. and Zhang, N.Z. (2010). Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics. JASA 105, 1202-1214.
    • (2010) JASA , vol.105 , pp. 1202-1214
    • Li, F.1    Zhang, N.Z.2
  • 13
    • 84860478382 scopus 로고    scopus 로고
    • A two-step penalized regression method with networked predictors
    • Luo, C., Pan, W., and Shen, X. (2012). A two-step penalized regression method with networked predictors. Statistics in Biosciences 4, 27-46.
    • (2012) Statistics in Biosciences , vol.4 , pp. 27-46
    • Luo, C.1    Pan, W.2    Shen, X.3
  • 14
    • 84860440017 scopus 로고    scopus 로고
    • Bayesian methods for network-structured genomics data
    • In, Honor of J. O. Berger, M.-H. Chen, D. K. Dey, P. Mueller, D. Sun, and K. Ye (eds), New York: Springer.
    • Monni, S. and Li, H. (2010). Bayesian methods for network-structured genomics data. In Frontiers of Statistical Decision Making and Bayesian Analysis, Honor of J. O. Berger, M.-H. Chen, D. K. Dey, P. Mueller, D. Sun, and K. Ye (eds), New York: Springer.
    • (2010) Frontiers of Statistical Decision Making and Bayesian Analysis
    • Monni, S.1    Li, H.2
  • 15
    • 65649099694 scopus 로고    scopus 로고
    • Network-based multiple locus linkage analysis of expression traits
    • Pan, W. (2009). Network-based multiple locus linkage analysis of expression traits. Bioinformatics 25(11), 1390-1396.
    • (2009) Bioinformatics , vol.25 , Issue.11 , pp. 1390-1396
    • Pan, W.1
  • 16
    • 77952976255 scopus 로고    scopus 로고
    • Incorporating predictor network in penalized regression with application to microarray data
    • Pan, W., Xie, B., and Shen, X. (2010). Incorporating predictor network in penalized regression with application to microarray data. Biometrics 66(2), 474-484.
    • (2010) Biometrics , vol.66 , Issue.2 , pp. 474-484
    • Pan, W.1    Xie, B.2    Shen, X.3
  • 17
    • 84864386991 scopus 로고    scopus 로고
    • Structured, sparse regression with application to HIV drug resistance
    • Percival, D., Roeder, K., Rosenfeld, R., and Wasserman, L. (2011). Structured, sparse regression with application to HIV drug resistance Annals of Applied Statistics 5(2A), 628-644
    • (2011) Annals of Applied Statistics , vol.5 , Issue.2 A , pp. 628-644
    • Percival, D.1    Roeder, K.2    Rosenfeld, R.3    Wasserman, L.4
  • 18
    • 9144236198 scopus 로고    scopus 로고
    • Human protein reference database as a discovery resource for proteomics
    • Wang, Y., Klijn, J.G., Zhang, Y., Sieuwerts, A.M., Look, M.P., Yang, F., Talantov, D., Timmermans, M., Meijer-van Gelder, M.E., Yu, J., Jatkoe, T., Berns, E.M., Atkins, D., and Foekens, J.A.
    • Wang, Y., Klijn, J.G., Zhang, Y., Sieuwerts, A.M., Look, M.P., Yang, F., Talantov, D., Timmermans, M., Meijer-van Gelder, M.E., Yu, J., Jatkoe, T., Berns, E.M., Atkins, D., and Foekens, J.A. (2004). Human protein reference database as a discovery resource for proteomics. Nucleic Acids Research 32(Database Issue), D497-D501.
    • (2004) Nucleic Acids Research , vol.32 , Issue.DATABASE ISSUE
  • 21
    • 84901206503 scopus 로고    scopus 로고
    • Bayesian variable selection in regression with networked predictors
    • In, T. Cai and X. Shen (eds), Beijing, China: Higher Education Press.
    • Tai, F., Pan, W., and Shen, X. (2010) Bayesian variable selection in regression with networked predictors. In Analysis of High Dimensional Data, T. Cai and X. Shen (eds), 147-165. Beijing, China: Higher Education Press.
    • (2010) Analysis of High Dimensional Data , pp. 147-165
    • Tai, F.1    Pan, W.2    Shen, X.3
  • 22
  • 26
    • 33645035051 scopus 로고    scopus 로고
    • Model selection and estimation in regression with grouped variables
    • Yuan, M. and Lin, Y. (2006). Model selection and estimation in regression with grouped variables. Journal of the Royal Statistical Society Series B 68, 49-67.
    • (2006) Journal of the Royal Statistical Society Series B , vol.68 , pp. 49-67
    • Yuan, M.1    Lin, Y.2
  • 27
    • 69949155103 scopus 로고    scopus 로고
    • The composite absolute penalties family for grouped and hierarchical variable selection
    • Zhao, P., Rocha, G., and Yu, B. (2009). The composite absolute penalties family for grouped and hierarchical variable selection. Annals of Statistics 37, 3468-3497.
    • (2009) Annals of Statistics , vol.37 , pp. 3468-3497
    • Zhao, P.1    Rocha, G.2    Yu, B.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.