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Volumn 26, Issue 19, 2010, Pages 2472-2473

BDVal: Reproducible large-scale predictive model development and validation in high-throughput datasets

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BIOLOGY; COMPUTER PROGRAM; DNA METHYLATION; GENETIC DATABASE; METHODOLOGY; VALIDATION STUDY;

EID: 77957228454     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btq463     Document Type: Article
Times cited : (8)

References (8)
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    • Gene selection for cancer classification using Support Vector Machines
    • Guyon,I. et al. (2002) Gene selection for cancer classification using Support Vector Machines. Mach. Learn., 46, 389-422.
    • (2002) Mach. Learn. , vol.46 , pp. 389-422
    • Guyon, I.1
  • 2
    • 40149090871 scopus 로고    scopus 로고
    • Microarray based diagnosis profits from better documentation of gene expression signatures
    • Kostka,D. and Spang,R. (2008) Microarray based diagnosis profits from better documentation of gene expression signatures. PLoS Comput. Biol., 4, e22.
    • (2008) PLoS Comput. Biol. , vol.4
    • Kostka, D.1    Spang, R.2
  • 3
    • 26444492840 scopus 로고    scopus 로고
    • Meeting the Challenges of Functional Genomics: From the Laboratory to the Clinic
    • Quackenbush, J. (2004) Meeting the Challenges of Functional Genomics: From the Laboratory to the Clinic. Preclinica, 2, 313-316.
    • (2004) Preclinica , vol.2 , pp. 313-316
    • Quackenbush, J.1
  • 4
    • 0000629975 scopus 로고
    • Cross-Validatory Choice and Assessment of Statistical Predictions
    • Stone,M. (1974) Cross-Validatory Choice and Assessment of Statistical Predictions. J. R. Stat. Soc. Ser. B (Methodological), 36, 111.
    • (1974) J. R. Stat. Soc. Ser. B (Methodological) , vol.36 , pp. 111
    • Stone, M.1
  • 5
    • 77957226516 scopus 로고    scopus 로고
    • A bias correction for the minimum error rate in cross-validation
    • Tibshirani,R.J. and Tibshirani,R. (2009) A bias correction for the minimum error rate in cross-validation. Appl. Stat., 822, 822-829.
    • (2009) Appl. Stat. , vol.822 , pp. 822-829
    • Tibshirani, R.J.1    Tibshirani, R.2
  • 6
    • 33644860703 scopus 로고    scopus 로고
    • Bias in error estimation when using cross-validation for model selection
    • Varma,S. and Simon,R. (2006) Bias in error estimation when using cross-validation for model selection. BMC Bioinformatics, 7, 91.
    • (2006) BMC Bioinformatics , vol.7 , pp. 91
    • Varma, S.1    Simon, R.2
  • 7
    • 0035184851 scopus 로고    scopus 로고
    • Biomarker identification by feature wrappers
    • Xiong,M. et al. (2001) Biomarker identification by feature wrappers. Genome Res., 11, 1878-1887.
    • (2001) Genome Res. , vol.11 , pp. 1878-1887
    • Xiong, M.1
  • 8
    • 78650735473 scopus 로고    scopus 로고
    • The MAQC-II Project: A comprehensive study of common practices for the development and validation of microarray-based predictive models. The MicroArray Quality Control
    • MAQC
    • MAQC. (2010) The MAQC-II Project: A comprehensive study of common practices for the development and validation of microarray-based predictive models. The MicroArray Quality Control. Nat. Biotechnol., 28, 827-838.
    • (2010) Nat. Biotechnol. , vol.28 , pp. 827-838


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