Robert J Tibshirani

Summary

Affiliation: Stanford University
Country: USA

Publications

  1. pmc Boolean implication networks derived from large scale, whole genome microarray datasets
    Debashis Sahoo
    Department of Computer Science, Stanford University, Stanford, CA 94305, USA
    Genome Biol 9:R157. 2008
  2. pmc Discovery and validation of breast cancer subtypes
    Amy V Kapp
    Department of Statistics, Stanford University, Stanford, CA, USA
    BMC Genomics 7:231. 2006
  3. pmc Cancer characterization and feature set extraction by discriminative margin clustering
    Kamesh Munagala
    Department of Biochemistry, Stanford University School of Medicine, 466 Gates Computer Science, Stanford, CA 94305, USA
    BMC Bioinformatics 5:21. 2004
  4. pmc 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns
    T Hastie
    Department of Statistics, Sequoia Hall, Stanford University, Stanford, CA 94305, USA
    Genome Biol 1:RESEARCH0003. 2000
  5. pmc Univariate shrinkage in the cox model for high dimensional data
    Robert J Tibshirani
    Stanford University, USA
    Stat Appl Genet Mol Biol 8:Article21. 2009
  6. ncbi request reprint Spatial smoothing and hot spot detection for CGH data using the fused lasso
    Robert Tibshirani
    Department of Health, Stanford University Stanford, CA 94305, USA
    Biostatistics 9:18-29. 2008
  7. ncbi request reprint Outlier sums for differential gene expression analysis
    Robert Tibshirani
    Department of Health Research and Policy, Stanford University, Stanford, CA 94305, USA
    Biostatistics 8:2-8. 2007
  8. pmc Diagnosis of multiple cancer types by shrunken centroids of gene expression
    Robert Tibshirani
    Department of Health, Research and Policy, and Statistics, Stanford University, Stanford, CA 94305, USA
    Proc Natl Acad Sci U S A 99:6567-72. 2002
  9. pmc Prediction of survival in diffuse large B-cell lymphoma based on the expression of 2 genes reflecting tumor and microenvironment
    Ash A Alizadeh
    Department of Medicine, Division of Oncology, Stanford University, Stanford, CA, USA
    Blood 118:1350-8. 2011
  10. pmc Predicting patient survival from longitudinal gene expression
    Yuping Zhang
    Stanford University, USA
    Stat Appl Genet Mol Biol 9:Article41. 2010

Detail Information

Publications17

  1. pmc Boolean implication networks derived from large scale, whole genome microarray datasets
    Debashis Sahoo
    Department of Computer Science, Stanford University, Stanford, CA 94305, USA
    Genome Biol 9:R157. 2008
    ..These relationships capture gender differences, tissue differences, development, and differentiation. New relationships are discovered that are preserved across all three species...
  2. pmc Discovery and validation of breast cancer subtypes
    Amy V Kapp
    Department of Statistics, Stanford University, Stanford, CA, USA
    BMC Genomics 7:231. 2006
    ..The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+...
  3. pmc Cancer characterization and feature set extraction by discriminative margin clustering
    Kamesh Munagala
    Department of Biochemistry, Stanford University School of Medicine, 466 Gates Computer Science, Stanford, CA 94305, USA
    BMC Bioinformatics 5:21. 2004
    ..A central challenge in the molecular diagnosis and treatment of cancer is to define a set of molecular features that, taken together, distinguish a given cancer, or type of cancer, from all normal cells and tissues...
  4. pmc 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns
    T Hastie
    Department of Statistics, Sequoia Hall, Stanford University, Stanford, CA 94305, USA
    Genome Biol 1:RESEARCH0003. 2000
    ..The technique can be 'unsupervised', that is, the genes and samples are treated as unlabeled, or partially or fully supervised by using known properties of the genes or samples to assist in finding meaningful groupings...
  5. pmc Univariate shrinkage in the cox model for high dimensional data
    Robert J Tibshirani
    Stanford University, USA
    Stat Appl Genet Mol Biol 8:Article21. 2009
    ..We illustrate the new method on real and simulated data, and compare it to other proposed methods for survival prediction with a large number of predictors...
  6. ncbi request reprint Spatial smoothing and hot spot detection for CGH data using the fused lasso
    Robert Tibshirani
    Department of Health, Stanford University Stanford, CA 94305, USA
    Biostatistics 9:18-29. 2008
    ..Estimates of false-discovery rate are also provided. Our studies show that the new method generally outperforms competing methods for calling gains and losses in CGH data...
  7. ncbi request reprint Outlier sums for differential gene expression analysis
    Robert Tibshirani
    Department of Health Research and Policy, Stanford University, Stanford, CA 94305, USA
    Biostatistics 8:2-8. 2007
    ..We also compare our approach to the recent cancer profile outlier analysis proposal of Tomlins and others (2005)...
  8. pmc Diagnosis of multiple cancer types by shrunken centroids of gene expression
    Robert Tibshirani
    Department of Health, Research and Policy, and Statistics, Stanford University, Stanford, CA 94305, USA
    Proc Natl Acad Sci U S A 99:6567-72. 2002
    ..The technique is general and can be used in many other classification problems. To demonstrate its effectiveness, we show that the method was highly efficient in finding genes for classifying small round blue cell tumors and leukemias...
  9. pmc Prediction of survival in diffuse large B-cell lymphoma based on the expression of 2 genes reflecting tumor and microenvironment
    Ash A Alizadeh
    Department of Medicine, Division of Oncology, Stanford University, Stanford, CA, USA
    Blood 118:1350-8. 2011
    ..We conclude that the measurement of a single gene expressed by tumor cells (LMO2) and a single gene expressed by the immune microenvironment (TNFRSF9) powerfully predicts overall survival in patients with DLBCL...
  10. pmc Predicting patient survival from longitudinal gene expression
    Yuping Zhang
    Stanford University, USA
    Stat Appl Genet Mol Biol 9:Article41. 2010
    ..Moreover, our method is consistently better than prediction methods using individual time point gene expression or simply pooling gene expression from each time point...
  11. ncbi request reprint Prognostic significance of VEGF, VEGF receptors, and microvessel density in diffuse large B cell lymphoma treated with anthracycline-based chemotherapy
    Dita Gratzinger
    Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305 5324, USA
    Lab Invest 88:38-47. 2008
    ..Dependence on autocrine vascular endothelial growth factor receptor-1-mediated signaling may render a subset of diffuse large B-cell lymphomas susceptible to anthracycline-based therapy...
  12. pmc In situ vaccination with a TLR9 agonist induces systemic lymphoma regression: a phase I/II study
    Joshua D Brody
    269 Campus Dr CCSR rm 1105, Stanford, CA 94305, USA
    J Clin Oncol 28:4324-32. 2010
    ..In a preclinical lymphoma model, intratumoral injection of a Toll-like receptor 9 (TLR9) agonist induced systemic antitumor immunity and cured large, disseminated tumors...
  13. pmc Molecular assessment of surgical-resection margins of gastric cancer by mass-spectrometric imaging
    Livia S Eberlin
    Department of Chemistry, Stanford University, Stanford, CA 94305 5080
    Proc Natl Acad Sci U S A 111:2436-41. 2014
    ..The results obtained suggest that DESI-MSI/Lasso may be valuable for routine intraoperative assessment of the specimen margins during gastric-cancer surgery. ..
  14. pmc Blood autoantibody and cytokine profiles predict response to anti-tumor necrosis factor therapy in rheumatoid arthritis
    Wolfgang Hueber
    Department of Medicine, Division of Immunology and Rheumatology, Stanford University, Stanford, CA 94305, USA
    Arthritis Res Ther 11:R76. 2009
    ..Since no clinical or laboratory tests are available to predict response to anti-TNF therapies, great need exists for predictive biomarkers...
  15. pmc Extensions of sparse canonical correlation analysis with applications to genomic data
    Daniela M Witten
    Stanford University, USA
    Stat Appl Genet Mol Biol 8:Article28. 2009
    ..We demonstrate these new methods on simulated data and on a recently published and publicly available diffuse large B-cell lymphoma data set...
  16. pmc Microvessel density and expression of vascular endothelial growth factor and its receptors in diffuse large B-cell lymphoma subtypes
    Dita Gratzinger
    Department of Pathology, Stanford University, Stanford, California, Stanford, CA 94305 5324, USA
    Am J Pathol 170:1362-9. 2007
    ..These differences may have important implications for the responsiveness of the two diffuse large B-cell lymphoma subtypes to anti-vascular endothelial growth factor and anti-angiogenic therapies...
  17. ncbi request reprint Polymorphisms in hypoxia inducible factor 1 and the initial clinical presentation of coronary disease
    Mark A Hlatky
    Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA 94305 5405, USA
    Am Heart J 154:1035-42. 2007
    ..The goal of this study was to assess whether polymorphisms in genes encoding elements of pathways mediating the response to ischemia affect vulnerability to MI among patients with underlying CAD...