137
Views
8
CrossRef citations to date
0
Altmetric
Original Articles

Identifying High-Dimensional Biomarkers for Personalized Medicine via Variable Importance Ranking

, , , , &
Pages 853-868 | Received 16 Oct 2007, Accepted 26 Feb 2008, Published online: 10 Sep 2008

REFERENCES

  • Ahn , H. , Moon , H. , Fazzari , M. J. , Lim , N. , Chen , J. J. , Kodell , R. L. ( 2007 ). Classification by ensembles from random partitions of high-dimensional data . Computational Statistics and Data Analysis 51 : 6166 – 6179 .
  • Alexandridis , R. , Lin , S. , Irwin , M. ( 2004 ). Class discovery and classification of tumor samples using mixture modeling of gene expression data—A unified approach . Bioinformatics 20 : 2545 – 2552 .
  • Alizadeh , A. A. , Elsen , M. B. , Davis , E. R. , Ma , C. , Lossos , I. S. , Rosenwald , A. , Boldrick , J. C. , Sabet , H. , Tran , T. , Yu , X. , Powell , J. I. , Yang , L. , Marti , G. E. , Moore , T. , Hudson Jr. , J. , Lu , L. , Lewis , D. B. , Tibshirani , R. , Sherlock , G. , Chan , W. C. , Greiner , T. C. , Weisenburger , D. D. , Armitage , J. O. , Warnke , R. , Levy , R. , Wilson , W. , Grever , M. R. , Byrd , J. C. , Botstein , D. , Brown , P. O. , Staudt , L. M. ( 2000 ). Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling . Nature 403 : 503 – 511 .
  • Blum , A. , Langley , P. ( 1997 ). Selection of relevant features and examples in machine learning . Artif. Intell. 97 : 245 – 271 .
  • Breiman , L. ( 1996 ). Bagging predictors . Machine Learning 24 : 123 – 140 .
  • Breiman , L. ( 2001 ). Random forest . Machine Learning 45 : 5 – 32 .
  • Breiman , L. , Friedman , J. H. , Olshen , R. A. , Stone , C. J. ( 1984 ). Classification and Regression Trees . California : Wadsworth .
  • Díaz-Uriarte , R. , de Andrés , A. ( 2006 ). Gene selection and classification of microarray data using random forest . BMC Bioinformatics 7 : 1 – 13 .
  • Dudoit , S. , Fridlyand , J. , Speed , T. P. ( 2002 ). Comparison of discrimination methods for the classification of tumors using gene expression data . J. Am. Statist. Assoc. 97 : 77 – 87 .
  • Freund , Y. ( 1990 ). Boosting a weak learning algorithm by majority . In: Proceedings of the Third Annual Workshop on Computational Learning Theory . San Mateo , CA : Morgan Kaufmann , pp. 202 – 216 .
  • Gordon , G. J. , Jensen , R. V. , Hsiao , L.-L. , Gullans , S. R. , Blumenstock , J. E. , Ramaswamy , S. , Richards , W. G. , Sugarbaker , D. J. , Bueno , R. ( 2002 ). Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma . Cancer Res. 62 : 4963 – 4967 .
  • Guyon , L. , Weston , J. , Barnhill , S. , Vapnik , V. ( 2002 ). Gene selection for cancer classification using support vector machines . Machine Learning 46 : 389 – 422 .
  • Hastie , T. , Tibshirani , R. , Sherlock , G. , Eisen , M. , Brown , P. , Botstein , D. ( 1999 ). Imputing Missing Data for Gene Expression Arrays . Technical report . Stanford , CA : Stanford University Statistics Department .
  • Ho , T. K. ( 1998 ). The random subspace method for constructing decision forests . IEEE Trans. Pattern Anal. Mach. Intell. 20 : 832 – 844 .
  • Kohavi , R. , John , G. H. ( 1997 ). Wrappers for feature subset selection . Artif. Intell. 97 : 273 – 324 .
  • Lee , J. W. , Lee , J. B. , Park , M. , Song , S. H. ( 2005 ). An extensive evaluation of recent classification tools applied to microarray data . Computational Statistics and Data Analysis 48 : 869 – 885 .
  • Liu , H. , Li , J. , Wong , L. ( 2002 ). A comparative study on feature selection and classification methods using gene expression profiles and proteomic patterns . Genome Inform. 13 : 51 – 60 .
  • Moon , H. , Ahn , H. , Kodell , R. L. , Baek , S. , Lin , C.-J. , Chen , J. J. ( 2007 ). Ensemble methods for classification of patients for personalized medicine with high-dimensional data . Artifi. Intell. Med. 41 : 197 – 207 .
  • Moon , H. , Ahn , H. , Kodell , R. L. , Lin , C.-J. , Baek , S. , Chen , J. J. ( 2006 ). Classification methods for the development of genomic signatures from high-dimensional data . Genome. Biol. 7 : R121.1 – R121.7 .
  • Schapire , R. ( 1990 ). Strength of weak learnability . J. Mach. Learning 5 : 197 – 227 .
  • Tibshirani , R. , Hastie , T. , Narasimhan , B. , Chu , G. (2002). Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl. Acad. Sci. USA 99:6567–6572.
  • Tsai , C.-A. , Chen , C.-H. , Lee , T.-C. , Ho , I.-C. , Yang , U.-C. , Chen , J. J. ( 2004 ). Gene selection for sample classifications in microarray experiments . DNA Cell Biol. 23 : 607 – 614 .
  • Wang , Y. , Tetko , I. V. , Hall , M. A. , Frank , E. , Facius , A. , Mayer , K. F. X. , Mewes , H. W. ( 2005 ). Gene selection from microarray data for cancer classification—a machine learning approach . Comput. Biol. Chem. 29 : 37 – 46 .
  • Yagi , T. , Morimoto , A. , Eguchi , M. , Hibi , S. , Sako , M. , Ishii , E. , Mizutani , S. , Imashuku , S. , Ohki , M. , Ichikawa , H. ( 2003 ). Identification of a gene expression signature associated with pediatric AML prognosis . Blood 102 : 1849 – 1856 .

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.