NETWORK-REGULARIZED HIGH-DIMENSIONAL COX REGRESSION FOR ANALYSIS OF GENOMIC DATA.
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Rui Feng | Wei Lin | Hongzhe Li | Hokeun Sun | Hongzhe Li | Wei Lin | Rui Feng | Hokeun Sun
[1] H. Zou,et al. Regularization and variable selection via the elastic net , 2005 .
[2] Hao Helen Zhang,et al. Adaptive Lasso for Cox's proportional hazards model , 2007 .
[3] Jiang Gui,et al. Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression data , 2005, Bioinform..
[4] Terence Tao,et al. The Dantzig selector: Statistical estimation when P is much larger than n , 2005, math/0506081.
[5] Edward J Oakeley,et al. WNT signaling enhances breast cancer cell motility and blockade of the WNT pathway by sFRP1 suppresses MDA-MB-231 xenograft growth , 2009, Breast Cancer Research.
[6] Trevor Hastie,et al. Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent. , 2011, Journal of statistical software.
[7] Peng Zhao,et al. On Model Selection Consistency of Lasso , 2006, J. Mach. Learn. Res..
[8] A. Fraser,et al. Systematic mapping of genetic interactions in Caenorhabditis elegans identifies common modifiers of diverse signaling pathways , 2006, Nature Genetics.
[9] Jon A. Wellner,et al. Weak Convergence and Empirical Processes: With Applications to Statistics , 1996 .
[10] Martin J. Wainwright,et al. Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$ -Constrained Quadratic Programming (Lasso) , 2009, IEEE Transactions on Information Theory.
[11] Fan Chung,et al. Spectral Graph Theory , 1996 .
[12] A. Ben-Baruch,et al. The inflammatory chemokines CCL2 and CCL5 in breast cancer. , 2008, Cancer letters.
[13] Jinchi Lv,et al. A unified approach to model selection and sparse recovery using regularized least squares , 2009, 0905.3573.
[14] R. Gill,et al. Cox's regression model for counting processes: a large sample study : (preprint) , 1982 .
[15] R. Tibshirani,et al. PATHWISE COORDINATE OPTIMIZATION , 2007, 0708.1485.
[16] R. Tibshirani. The lasso method for variable selection in the Cox model. , 1997, Statistics in medicine.
[17] Bin Nan,et al. Hierarchically penalized Cox regression with grouped variables , 2009 .
[18] Jinchi Lv,et al. High-Dimensional Sparse Additive Hazards Regression , 2012, 1212.6232.
[19] Federico Garrido,et al. The selection of tumor variants with altered expression of classical and nonclassical MHC class I molecules: implications for tumor immune escape , 2004, Cancer Immunology, Immunotherapy.
[20] J. Foekens,et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer , 2005, The Lancet.
[21] Larry Norton,et al. Latent bone metastasis in breast cancer tied to Src-dependent survival signals. , 2009, Cancer cell.
[22] 中尾 光輝,et al. KEGG(Kyoto Encyclopedia of Genes and Genomes)〔和文〕 (特集 ゲノム医学の現在と未来--基礎と臨床) -- (データベース) , 2000 .
[23] Charles R. Johnson,et al. Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.
[24] Hongzhe Li,et al. VARIABLE SELECTION AND REGRESSION ANALYSIS FOR GRAPH-STRUCTURED COVARIATES WITH AN APPLICATION TO GENOMICS. , 2010, The annals of applied statistics.
[25] O. Rath,et al. MAP kinase signalling pathways in cancer , 2007, Oncogene.
[26] H. Putter,et al. HLA-E and HLA-G Expression in Classical HLA Class I-Negative Tumors Is of Prognostic Value for Clinical Outcome of Early Breast Cancer Patients , 2010, The Journal of Immunology.
[27] David R. Cox,et al. Regression models and life tables (with discussion , 1972 .
[28] W. Hoeffding. Probability Inequalities for sums of Bounded Random Variables , 1963 .
[29] Robert A. Weinberg,et al. A Pleiotropically Acting MicroRNA, miR-31, Inhibits Breast Cancer Metastasis , 2009 .
[30] Yichao Wu. ELASTIC NET FOR COX'S PROPORTIONAL HAZARDS MODEL WITH A SOLUTION PATH ALGORITHM. , 2012, Statistica Sinica.
[31] M. Kosorok. Introduction to Empirical Processes and Semiparametric Inference , 2008 .
[32] Cun-Hui Zhang,et al. ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL. , 2013, Annals of statistics.
[33] Jian Huang,et al. The Sparse Laplacian Shrinkage Estimator for High-Dimensional Regression. , 2011, Annals of statistics.
[34] Mohamed Hebiri,et al. The Smooth-Lasso and other $\ell_1+\ell_2$-penalized methods , 2010, 1003.4885.
[35] P. Massart,et al. Concentration inequalities and model selection , 2007 .
[36] Jianqing Fan,et al. REGULARIZATION FOR COX'S PROPORTIONAL HAZARDS MODEL WITH NP-DIMENSIONALITY. , 2010, Annals of statistics.
[37] Wei Pan,et al. Incorporating Predictor Network in Penalized Regression with Application to Microarray Data , 2010, Biometrics.
[38] S. Kong,et al. Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso. , 2012, Statistica Sinica.
[39] Anestis Antoniadis,et al. The Dantzig Selector in Cox's Proportional Hazards Model , 2009 .
[40] Jianqing Fan,et al. Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties , 2001 .
[41] H. Zou. The Adaptive Lasso and Its Oracle Properties , 2006 .
[42] Yi Li,et al. Statistical Applications in Genetics and Molecular Biology Survival Analysis with High-Dimensional Covariates : An Application in Microarray Studies , 2011 .
[43] S. Geer,et al. The Smooth-Lasso and other ℓ1+ℓ2-penalized methods , 2011 .
[44] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[45] K. Lange,et al. Coordinate descent algorithms for lasso penalized regression , 2008, 0803.3876.
[46] Kun-Liang Guan,et al. Isolation and Characterization of a Novel Dual Specific Phosphatase, HVH2, Which Selectively Dephosphorylates the Mitogen-activated Protein Kinase (*) , 1995, The Journal of Biological Chemistry.
[47] Jianqing Fan,et al. Variable Selection for Cox's proportional Hazards Model and Frailty Model , 2002 .