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J. S. Marron

Active 1983–2025

170
Papers
32,402
Citations
68
h-index
138
i10-index

Citations

Citations per year for J. S. Marron1983: 1 citations1984: 1 citations1985: 2 citations1986: 2 citations1987: 17 citations1988: 11 citations1989: 8 citations1990: 26 citations1991: 38 citations1992: 34 citations1993: 35 citations1994: 53 citations1995: 47 citations1996: 55 citations1997: 62 citations1998: 35 citations1999: 74 citations2000: 64 citations2001: 68 citations2002: 110 citations2003: 124 citations2004: 203 citations2005: 255 citations2006: 318 citations2007: 384 citations2008: 423 citations2009: 470 citations2010: 534 citations2011: 558 citations2012: 519 citations2013: 595 citations2014: 518 citations2015: 569 citations2016: 563 citations2017: 479 citations2018: 504 citations2019: 885 citations2020: 870 citations2021: 923 citations2022: 707 citations2023: 576 citations2024: 607 citations2025: 402 citations2026: 97 citations

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 4,323 citing papers, 28.3% of this breakdownChina: 1,228 citing papers, 8% of this breakdownUnited Kingdom: 1,090 citing papers, 7.1% of this breakdownGermany: 751 citing papers, 4.9% of this breakdownCanada: 726 citing papers, 4.8% of this breakdownFrance: 617 citing papers, 4% of this breakdownItaly: 505 citing papers, 3.3% of this breakdownSpain: 476 citing papers, 3.1% of this breakdownAustralia: 474 citing papers, 3.1% of this breakdownNetherlands: 359 citing papers, 2.4% of this breakdownJapan: 342 citing papers, 2.3% of this breakdownIndia: 321 citing papers, 2.1% of this breakdown
0%28.3%Other 26.6%

Institutions

Fields

  • Computer Science34.2%
  • Biochemistry, Genetics and Molecular Biology26.9%
  • Medicine14.1%
  • Mathematics11.4%
  • Engineering4%
  • Neuroscience1.4%
  • Other8%

Topics

  • AI in cancer detection3.9%
  • Breast Cancer Treatment Studies3.8%
  • Statistical Methods and Inference3.5%
  • Gene expression and cancer classification3.5%
  • Software Engineering Research3%
  • Bayesian Methods and Mixture Models2.3%
  • Other80%

Coauthors

All papers

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  1. Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes

    Authors: Joel S. Parker, Michael E. Mullins, Maggie C.U. Cheang, Samuel Leung, David Voduc, Tammi L. Vickery, Sherri R. Davies, Christiane Fauron, Xiaping He, Zhiyuan Hu, John F. Quackenbush, Inge J. Stijleman, Juan Palazzo, J. S. Marron, Andrew B. Nobel, Elaine R. Mardis, Torsten O. Nielsen, Matthew J. Ellis, Charles M. Perou, Philip S. Bernard - Journal of Clinical Oncology 2009 cited by 4,887

  2. A Method for Normalizing Histology Slides for Quantitative Analysis

    Authors: Marc Macenko, Marc Niethammer, J. S. Marron, David Borland, John T. Woosley, Xiaojun Guan, Charles Schmitt, Nancy E. Thomas - IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 cited by 1,330

  3. Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype

    Authors: Heather D. Couture, Lindsay A. Williams, Joseph Geradts, Sarah J. Nyante, Eboneé N. Butler, J. S. Marron, Charles M. Perou, Melissa A. Troester, Marc Niethammer - npj Breast Cancer 2018 cited by 333

  4. Repeated observation of breast tumor subtypes in independent gene expression data sets

    Authors: Thérese Sørlie, Robert Tibshirani, Joel S. Parker, Trevor Hastie, J. S. Marron, Andrew B. Nobel, Shibing Deng, Hilde Johnsen, Robert Pesich, Stephanie Geisler, János Demeter, Charles M. Perou, Per Eystein Lønning, Patrick O. Brown, Anne‐Lise Børresen‐Dale, David Botstein - National Academy of Sciences, Proceedings of the National Academy of Sciences 2003 cited by 5,411

  5. Joint and individual variation explained (JIVE) for integrated analysis of multiple data types

    Authors: Eric F. Lock, Katherine A. Hoadley, J. S. Marron, Andrew B. Nobel - The Annals of Applied Statistics 2013 cited by 591

  6. Persistent homology analysis of brain artery trees

    Authors: Paul Bendich, J. S. Marron, Ezra Miller, Alex Pieloch, Sean Skwerer - The Annals of Applied Statistics 2016 cited by 269

  7. Geometric Representation of High Dimension, Low Sample Size Data

    Authors: Peter A. Hall, J. S. Marron, Amnon Neeman - Journal of the Royal Statistical Society Series B (Statistical Methodology) 2005 cited by 502

  8. Predicting Fault Incidence Using Software Change History

    Authors: Todd L. Graves, Alan F. Karr, J. S. Marron, Harvey P. Siy - IEEE Transactions on Software Engineering, IEEE Trans. Software Eng. 2000 cited by 751

  9. Does Code Decay? Assessing the Evidence from Change Management Data

    Authors: Stephen G. Eick, Todd L. Graves, Alan F. Karr, J. S. Marron, Audris Mockus - IEEE Transactions on Software Engineering, IEEE Trans. Software Eng. 2001 cited by 641

  10. Statistical Significance of Clustering for High-Dimension, Low–Sample Size Data

    Authors: Yufeng Liu, D. Neil Hayes, Andrew B. Nobel, J. S. Marron - Journal of the American Statistical Association 2008 cited by 281

  11. Distance-Weighted Discrimination

    Authors: J. S. Marron, Michael J. Todd, Jeongyoun Ahn - Journal of the American Statistical Association 2007 cited by 327

  12. A Brief Survey of Bandwidth Selection for Density Estimation

    Authors: M. C. Jones, J. S. Marron, Simon J. Sheather - Journal of the American Statistical Association 1996 cited by 1,249

  13. Exact Mean Integrated Squared Error

    Authors: J. S. Marron, M. P. Wand - The Annals of Statistics 1992 cited by 765

  14. Comparison of Data-Driven Bandwidth Selectors

    Authors: Byeong U. Park, J. S. Marron - Journal of the American Statistical Association 1990 cited by 488

  15. The molecular portraits of breast tumors are conserved across microarray platforms

    Authors: Maria Tretiakova, Matthew G. Ewend, Michael Mullins, Chad Livasy, Heidi J. Hansen, Mary C. Mone, Rita Nanda, Joel S. Parker, Edward Nelson, Lynn G. Dressler, J. S. Marron, Evangeline Reynolds, Cheng Fan, Charles M. Perou, Alejandra Ruiz Orrico, Laurent Perreard, Junyuan Wu, Philip S. Bernard, John F. Quackenbush, Yudong Liu, Zhiyuan Hu, Lynda Sawyer, Andrew B. Nobel, Daniel Oh, Juan Palazzo, Matthew J. Ellis, Xiaping He, Lisa A. Carey, Bahjat F. Qaqish, Olufunmilayo I. Olopade, Donna Dreher - BMC Genomics 2006 cited by 1,470

  16. Robust principal component analysis for functional data

    Authors: Nicholas Locantore, J. S. Marron, Douglas G. Simpson, N. Tripoli, J. T. Zhang, K. L. Cohen, Graciela Boente, Ricardo Fraiman, Babette Brumback, Christophe Croux, Jianqing Fan, Aloïs Kneip, John I. Marden, Daniel Peña, Javier Prieto, Jim O. Ramsay, Mariano J. Valderrama, Ana M. Aguilera, Nicholas Locantore, J. S. Marron, Douglas G. Simpson, N. Tripoli, J. T. Zhang, K. L. Cohen - Test 1999 cited by 371

  17. PCA consistency in high dimension, low sample size context

    Authors: Sungkyu Jung, J. S. Marron - The Annals of Statistics 2009 cited by 311

  18. A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium

    Authors: Amanda E. Nelson, Fei Fang, Liubov Arbeeva, R.J. Cleveland, Todd A. Schwartz, Leigh F. Callahan, J. S. Marron, Richard F. Loeser - Osteoarthritis and Cartilage 2019 cited by 100

  19. Analysis of principal nested spheres

    Authors: Sang‐Hun Jung, Ian L. Dryden, J. S. Marron - Biometrika 2012 cited by 160

  20. MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data

    Authors: Siyao Liu, Aatish Thennavan, Joseph P. Garay, J. S. Marron, Charles M. Perou - Genome biology 2021 cited by 49

  21. Registration of Functional Data Using Fisher-Rao Metric

    Authors: Anuj Srivastava, Wei Wu, Sebastian Kurtek, Eric Klassen, J. S. Marron - arXiv (Cornell University) 2011 cited by 158

  22. Angle-based joint and individual variation explained

    Authors: Qing Feng, Meilei Jiang, Jan Hannig, J. S. Marron - Journal of Multivariate Analysis, J. Multivar. Anal. 2018 cited by 99

  23. Local polynomial regression for symmetric positive definite matrices

    Authors: Ying Yuan, Hongtu Zhu, Weili Lin, J. S. Marron - Journal of the Royal Statistical Society Series B (Statistical Methodology) 2012 cited by 88

  24. Predicting early breast cancer recurrence from histopathological images in the Carolina Breast Cancer Study

    Authors: Yifeng Shi, Linnea T. Olsson, Katherine A. Hoadley, Benjamin C. Calhoun, J. S. Marron, Joseph Geradts, Marc Niethammer, Melissa A. Troester - npj Breast Cancer 2023 cited by 17