Reporting bias when using real data sets to analyze classification performance

Bioinformatics

Volumn 26, Issue 1, 2009, Pages 68-76

  Yousefi, Mohammadmahdi R ^a   Hua, Jianping ^b   Sima, Chao ^b   Dougherty, Edward R ^a,b  

^a Texas AandM University   (United States)

^b TRANSLATIONAL GENOMICS RESEARCH INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 75249095400     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btp605     Document Type: Article

References (20)

1. Bhattacharjee, A. et al. (2001) Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc. Natl Acad. Sci. USA, 98, 13790-13795.
2. Braga-Neto, U.M. and Dougherty, E.R. (2004) Is cross-validation valid for small-sample microarray classification? Bioinformatics, 20, 374-380.
3. Chen, X. et al. (2004) Novel endothelial cell markers in hepatocellular carcinoma. Modern Pathol., 17, 1198-1210.
4. Desmedt, C. et al. (2007) Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series. Clin. Cancer Res., 13, 3207-3214.
5. Dougherty, E.R. et al. (2007) Validation of computational methods in genomics. Curr. Genomics, 8, 1-19.
6. Glick, N. (1978) Additive estimators for probabilities of correct classification. Pattern Recogn., 10, 211-222.
7. Hanczar, B. et al. (2007) Decorrelation of the true and estimated classifier errors in high-dimensional settings. EURASIP J. Bioinform. Syst. Biol., Article ID 38473.
8. Hua, J. et al. (2009) Performance of feature selection methods in the classification of high-dimensional data. Pattern Recogn., 42, 409-424.
9. Natsoulis, G. et al. (2005) Classification of a large microarray data set: algorithm comparison and analysis of drug signatures. Genome Res., 15, 724-736.
10. Potti, A. et al. (2006) A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N. Eng. J. Med., 355, 570-580.
11. Rosenwald, A. et al. (2002) The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N. Eng. J. Med., 346, 1937-1947.
12. Shmulevich, I. and Dougherty, E.R. (2007) Genomic Signal Processing. Princeton University Press, Princeton.
13. Sima, C. and Dougherty, E.R. (2006) What should be expected from feature selection in small-sample settings. Bioinformatics, 22, 2430-2436.
14. Sima, C. et al. (2005) Impact of error estimation on feature-selection algorithms. Pattern Recogn., 38, 2472-2482.
15. Su, A.I. et al. (2001) Molecular classification of human carcinomas by use of gene expression signatures. Cancer Res., 61, 7388-7393.
16. Valk, P.J. et al. (2004) Prognostically useful gene-expression profiles in acute myeloid leukemia. N. Eng. J. Med., 350, 1617-1628.
17. van de Vijver, M.J. et al. (2002) A gene-expression signature as a predictor of survival in breast cancer. N. Eng. J. Med., 347, 1999-2009.
18. Wang, Y. et al. (2005) Gene-expression profiles to predict distant metastasis of lymphnode-negative primary breast cancer. Lancet, 365, 671-679.
19. Yeoh, E.J. et al. (2002) Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell, 1, 133-143.
20. Zhan, F. et al. (2006) The molecular classification of multiple myeloma. Blood, 108, 2020-2028.