| Supervised risk predictor of breast cancer based on intrinsic subtypes JS Parker, M Mullins, MCU Cheang, S Leung, D Voduc, T Vickery, ... Journal of clinical oncology 27 (8), 1160-1167, 2009 | 5459 | 2009 |
| Comprehensive genomic characterization of squamous cell lung cancers Cancer Genome Atlas Research Network Nature 489 (7417), 519, 2012 | 3846 | 2012 |
| Comprehensive genomic characterization of head and neck squamous cell carcinomas Cancer Genome Atlas Network Nature 517 (7536), 576, 2015 | 3528 | 2015 |
| The molecular portraits of breast tumors are conserved across microarray platforms Z Hu, C Fan, DS Oh, JS Marron, X He, BF Qaqish, C Livasy, LA Carey, ... BMC genomics 7, 1-12, 2006 | 1934 | 2006 |
| A brief survey of bandwidth selection for density estimation MC Jones, JS Marron, SJ Sheather Journal of the American statistical association 91 (433), 401-407, 1996 | 1814 | 1996 |
| A method for normalizing histology slides for quantitative analysis M Macenko, M Niethammer, JS Marron, D Borland, JT Woosley, X Guan, ... 2009 IEEE international symposium on biomedical imaging: from nano to macro …, 2009 | 1499 | 2009 |
| Repeated observation of breast tumor subtypes in independent gene expression data sets T Sørlie, R Tibshirani, J Parker, T Hastie, JS Marron, A Nobel, S Deng, ... Proceedings of the national academy of sciences 100 (14), 8418-8423, 2003 | 1176 | 2003 |
| Predicting fault incidence using software change history TL Graves, AF Karr, JS Marron, H Siy IEEE Transactions on software engineering 26 (7), 653-661, 2000 | 1051 | 2000 |
| Exact mean integrated squared error JS Marron, MP Wand The Annals of Statistics 20 (2), 712-736, 1992 | 1040 | 1992 |
| Does code decay? assessing the evidence from change management data SG Eick, TL Graves, AF Karr, JS Marron, A Mockus IEEE transactions on software engineering 27 (1), 1-12, 2001 | 860 | 2001 |
| SiZer for exploration of structures in curves P Chaudhuri, JS Marron Journal of the American Statistical Association 94 (447), 807-823, 1999 | 785 | 1999 |
| Comparison of data-driven bandwidth selectors BU Park, JS Marron Journal of the American Statistical Association 85 (409), 66-72, 1990 | 733 | 1990 |
| Optimal bandwidth selection in nonparametric regression function estimation W Härdle, JS Marron The Annals of Statistics, 1465-1481, 1985 | 639 | 1985 |
| Geometric representation of high dimension, low sample size data P Hall, JS Marron, A Neeman Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2005 | 636 | 2005 |
| Joint and individual variation explained (JIVE) for integrated analysis of multiple data types EF Lock, KA Hoadley, JS Marron, AB Nobel The annals of applied statistics 7 (1), 523, 2013 | 631 | 2013 |
| How far are automatically chosen regression smoothing parameters from their optimum? W Härdle, P Hall, JS Marron Journal of the American Statistical Association 83 (401), 86-95, 1988 | 615 | 1988 |
| Adjustment of systematic microarray data biases M Benito, J Parker, Q Du, J Wu, D Xiang, CM Perou, JS Marron Bioinformatics 20 (1), 105-114, 2004 | 517 | 2004 |
| Robust principal component analysis for functional data N Locantore, JS Marron, DG Simpson, N Tripoli, JT Zhang, KL Cohen, ... Test 8, 1-73, 1999 | 471 | 1999 |
| Characterization of HPV and host genome interactions in primary head and neck cancers M Parfenov, CS Pedamallu, N Gehlenborg, SS Freeman, L Danilova, ... Proceedings of the National Academy of Sciences 111 (43), 15544-15549, 2014 | 448 | 2014 |
| Distance-weighted discrimination JS Marron, MJ Todd, J Ahn Journal of the American Statistical Association 102 (480), 1267-1271, 2007 | 437 | 2007 |
Charles M. PerouUniversity of North Carolina at Chapel HillVerified email at med.unc.edu
