메뉴 건너뛰기




Volumn 28, Issue 21, 2012, Pages 2824-2833

Performance reproducibility index for classification

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER;

EID: 84868014796     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/bts509     Document Type: Article
Times cited : (9)

References (37)
  • 2
    • 77949535610 scopus 로고    scopus 로고
    • Over-optimism in bioinformatics research
    • Boulesteix, A.-L. (2010) Over-optimism in bioinformatics research. Bioinformatics, 26, 437-33.
    • (2010) Bioinformatics , vol.26 , pp. 437-533
    • Boulesteix, A.-L.1
  • 3
    • 69249085408 scopus 로고    scopus 로고
    • Stability and aggregation of ranked gene lists
    • Boulesteix, A.-L. and Slawski, M. (2009) Stability and aggregation of ranked gene lists. Brief. Bioinform., 10, 556-33.
    • (2009) Brief. Bioinform. , vol.10 , pp. 556-633
    • Boulesteix, A.-L.1    Slawski, M.2
  • 4
    • 1342330535 scopus 로고    scopus 로고
    • Is cross-validation valid for small-sample microarray classification?
    • Braga-Neto, U.M. and Dougherty, E.R. (2004) Is cross-validation valid for small-sample microarray classification? Bioinformatics, 20, 374-33.
    • (2004) Bioinformatics , vol.20 , pp. 374-433
    • Braga-Neto, U.M.1    Dougherty, E.R.2
  • 5
    • 75149170858 scopus 로고    scopus 로고
    • Exact correlation between actual and estimated errors in discrete classification
    • Braga-Neto, U.M. and Dougherty, E.R. (2010) Exact correlation between actual and estimated errors in discrete classification. Pattern Recognit. Lett., 31, 407-33.
    • (2010) Pattern Recognit. Lett. , vol.31 , pp. 407-433
    • Braga-Neto, U.M.1    Dougherty, E.R.2
  • 6
    • 79955760409 scopus 로고    scopus 로고
    • An empirical assessment of validation practices for molecular classifiers
    • Castaldi, P.J. et al. (2011) An empirical assessment of validation practices for molecular classifiers. Brief. Bioinform., 12, 189-33.
    • (2011) Brief. Bioinform. , vol.12 , pp. 189-233
    • Castaldi, P.J.1
  • 7
    • 4744347276 scopus 로고    scopus 로고
    • Novel endothelial cell markers in hepatocellular carcinoma
    • Chen, X. et al. (2004) Novel endothelial cell markers in hepatocellular carcinoma. Modern Pathol., 17, 1198-33.
    • (2004) Modern Pathol. , vol.17 , pp. 1198-2143
    • Chen, X.1
  • 8
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes, C. and Vapnik, V.N. (1995) Support-vector networks. Mach. Learn., 20, 273-33.
    • (1995) Mach. Learn. , vol.20 , pp. 273-333
    • Cortes, C.1    Vapnik, V.N.2
  • 9
    • 79959465085 scopus 로고    scopus 로고
    • Bayesian minimum mean-square error estimation for classification error-part i: Definition and the bayesian mmse error estimator for discrete classification
    • Dalton, L.A. and Dougherty, E.R. (2011a) Bayesian minimum mean-square error estimation for classification error-Part I: Definition and the Bayesian MMSE error estimator for discrete classification. IEEE Trans. Signal Process., 59, 115-33.
    • (2011) IEEE Trans. Signal Process. , vol.59 , pp. 115-133
    • Dalton, L.A.1    Dougherty, E.R.2
  • 10
    • 79959412679 scopus 로고    scopus 로고
    • Application of the Bayesian MMSE error estimator for classification error to gene-expression microarray data
    • Dalton, L.A. and Dougherty, E.R. (2011b) Application of the Bayesian MMSE error estimator for classification error to gene-expression microarray data. Bioinformatics, 27, 1822-33.
    • (2011) Bioinformatics , vol.27 , pp. 1822-1833
    • Dalton, L.A.1    Dougherty, E.R.2
  • 11
    • 84859950916 scopus 로고    scopus 로고
    • Exact MSE performance of the bayesian MMSE estimator for classification error-part ii: Consistency and performance analysis
    • Dalton, L.A. and Dougherty, E.R. (2012a) Exact MSE performance of the Bayesian MMSE estimator for classification error-Part II: Consistency and performance analysis. IEEE Trans. Signal Process., 60, 2588-33.
    • (2012) IEEE Trans. Signal Process. , vol.60 , pp. 2588-3543
    • Dalton, L.A.1    Dougherty, E.R.2
  • 12
    • 84857044891 scopus 로고    scopus 로고
    • Optimal MSE calibration of error estimators under Bayesian models
    • Dalton, L.A. and Dougherty, E.R. (2012b) Optimal MSE calibration of error estimators under Bayesian models. Pattern Recognit., 45, 2308-33.
    • (2012) Pattern Recognit. , vol.45 , pp. 2308-2333
    • Dalton, L.A.1    Dougherty, E.R.2
  • 14
    • 79955765957 scopus 로고    scopus 로고
    • Validation of gene regulatory networks: Scientific and inferential
    • Dougherty, E.R. (2011) Validation of gene regulatory networks: scientific and inferential. Brief. Bioinform., 12, 245-33.
    • (2011) Brief. Bioinform. , vol.12 , pp. 245-333
    • Dougherty, E.R.1
  • 15
    • 84858291678 scopus 로고    scopus 로고
    • Prudence, risk, and reproducibility in biomarker discovery
    • Dougherty, E.R. (2012) Prudence, risk, and reproducibility in biomarker discovery. BioEssays, 34, 277-33.
    • (2012) BioEssays , vol.34 , pp. 277-333
    • Dougherty, E.R.1
  • 17
    • 77950126816 scopus 로고    scopus 로고
    • Performance of error estimators for classification
    • Dougherty, E.R. et al. (2010) Performance of error estimators for classification. Curr. Bioinform., 5, 53-33.
    • (2010) Curr. Bioinform. , vol.5 , pp. 53-33
    • Dougherty, E.R.1
  • 18
    • 79961007365 scopus 로고    scopus 로고
    • The illusion of distribution-free small-sample classification in genomics
    • Dougherty, E.R. et al. (2011) The illusion of distribution-free small-sample classification in genomics. Curr. Genomics, 12, 333-33.
    • (2011) Curr. Genomics , vol.12 , pp. 333-433
    • Dougherty, E.R.1
  • 20
    • 37649015028 scopus 로고    scopus 로고
    • Decorrelation of the true and estimated classifier errors in high-dimensional settings
    • Hanczar, B. et al. (2007) Decorrelation of the true and estimated classifier errors in high-dimensional settings. EURASIP J. Bioinform. Syst. Biol., 2007, 12.
    • (2007) EURASIP J. Bioinform. Syst. Biol. , vol.2007 , pp. 12
    • Hanczar, B.1
  • 21
    • 77951964158 scopus 로고    scopus 로고
    • Small-sample precision of ROC-related estimates
    • Hanczar, B. et al. (2010) Small-sample precision of ROC-related estimates. Bioinformatics, 26, 822-33.
    • (2010) Bioinformatics , vol.26 , pp. 822-833
    • Hanczar, B.1
  • 22
    • 17544364191 scopus 로고    scopus 로고
    • Optimal number of features as a function of sample size for various classification rules
    • Hua, J. et al. (2005) Optimal number of features as a function of sample size for various classification rules. Bioinformatics, 21, 1509-33.
    • (2005) Bioinformatics , vol.21 , pp. 1509-1533
    • Hua, J.1
  • 23
    • 79955753954 scopus 로고    scopus 로고
    • Case studies in reproducibility
    • Hothorn, T. and Leisch, F. (2011) Case studies in reproducibility. Brief. Bioinform., 12, 288-33.
    • (2011) Brief. Bioinform , vol.12 , pp. 288-333
    • Hothorn, T.1    Leisch, F.2
  • 24
    • 33846563409 scopus 로고    scopus 로고
    • Why most published research findings are false
    • Ioannidis, J.P.A. (2005) Why most published research findings are false. PLoS Med, 2, e124.
    • (2005) PLoS Med , vol.2
    • Ioannidis, J.P.A.1
  • 25
    • 77955362768 scopus 로고    scopus 로고
    • Over-optimism in bioinformatics: An illustration
    • Jelizarow, M. et al. (2010) Over-optimism in bioinformatics: an illustration. Bioinformatics, 26, 1990-33.
    • (2010) Bioinformatics , vol.26 , pp. 1990-2943
    • Jelizarow, M.1
  • 26
    • 79955564639 scopus 로고    scopus 로고
    • Measuring reproducibility of high-throughput experiments
    • Li, Q. et al. (2011) Measuring reproducibility of high-throughput experiments. Ann. Appl. Stat., 5, 1752-33.
    • (2011) Ann. Appl. Stat. , vol.5 , pp. 1752-2743
    • Li, Q.1
  • 27
    • 21144462902 scopus 로고    scopus 로고
    • Classification of a large microarray data set: Algorithm comparison and analysis of drug signatures
    • Natsoulis, G. et al. (2005) Classification of a large microarray data set: algorithm comparison and analysis of drug signatures. Genome Res., 15, 724-33.
    • (2005) Genome Res. , vol.15 , pp. 724-733
    • Natsoulis, G.1
  • 28
    • 84878566735 scopus 로고    scopus 로고
    • FDA's woodcock says personalized drug development entering 'long slog' phase
    • 26 October 2011, date last accessed
    • Ray, T. (2011) FDA's Woodcock says personalized drug development entering 'long slog' phase. Pharmacogen. Rep., http://www.genomeweb.com/mdx/fdas- woodcock-says-personalized-drug-development-entering-long-slog-phase (26 October 2011, date last accessed).
    • (2011) Pharmacogen. Rep
    • Ray, T.1
  • 29
    • 84872686063 scopus 로고    scopus 로고
    • Proteomics in melanoma biomarker discovery: Great potential, many obstacles
    • Sabel, M.S. et al. (2011) Proteomics in melanoma biomarker discovery: great potential, many obstacles. Int. J. Proteom., 2011, 8.
    • (2011) Int. J. Proteom. , vol.2011 , pp. 8
    • Sabel, M.S.1
  • 30
    • 19044399684 scopus 로고    scopus 로고
    • Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling
    • 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, 133-33.
    • (2002) Cancer Cell , vol.1 , pp. 133-233
    • Yeoh, E.J.1
  • 31
    • 75249095400 scopus 로고    scopus 로고
    • Reporting bias when using real data sets to analyze classification performance
    • Yousefi, M.R. et al. (2010) Reporting bias when using real data sets to analyze classification performance. Bioinformatics, 26, 68-33.
    • (2010) Bioinformatics , vol.26 , pp. 68-33
    • Yousefi, M.R.1
  • 32
    • 79958131021 scopus 로고    scopus 로고
    • Multiple-rule bias in the comparison of classification rules
    • Yousefi, M.R. et al. (2011) Multiple-rule bias in the comparison of classification rules. Bioinformatics, 27, 1675-33.
    • (2011) Bioinformatics , vol.27 , pp. 1675-2643
    • Yousefi, M.R.1
  • 33
    • 33745779502 scopus 로고    scopus 로고
    • The molecular classification of multiple myeloma
    • Zhan, F. et al. (2006) The molecular classification of multiple myeloma. Blood, 108, 2020-33.
    • (2006) Blood , vol.108 , pp. 2020-2033
    • Zhan, F.1
  • 34
    • 51749123784 scopus 로고    scopus 로고
    • Apparently low reproducibility of true differential expression discoveries in microarray studies
    • Zhang, M. et al. (2008) Apparently low reproducibility of true differential expression discoveries in microarray studies. Bioinformatics, 24, 2057-33.
    • (2008) Bioinformatics , vol.24 , pp. 2057-3043
    • Zhang, M.1
  • 35
    • 67649205714 scopus 로고    scopus 로고
    • Evaluating reproducibility of differential expression discoveries in microarray studies by considering correlated molecular changes
    • Zhang, M. et al. (2009) Evaluating reproducibility of differential expression discoveries in microarray studies by considering correlated molecular changes. Bioinformatics, 25, 1662-33.
    • (2009) Bioinformatics , vol.25 , pp. 1662-2643
    • Zhang, M.1
  • 36
    • 77649305686 scopus 로고    scopus 로고
    • Joint sampling distribution between actual and estimated classification errors for linear discriminant analysis
    • Zollanvari, A. et al. (2010) Joint sampling distribution between actual and estimated classification errors for linear discriminant analysis. IEEE Trans. Inform. Theory, 56, 784-33.
    • (2010) IEEE Trans. Inform. Theory , vol.56 , pp. 784-833
    • Zollanvari, A.1
  • 37
    • 80052964854 scopus 로고    scopus 로고
    • Exact representation of the second-order moments for resubstitution and leave-one-out error estimation for linear discriminant analysis in the univariate heteroskedastic Gaussian model
    • Zollanvari, A. et al. (2012) Exact representation of the second-order moments for resubstitution and leave-one-out error estimation for linear discriminant analysis in the univariate heteroskedastic Gaussian model. Pattern Recognit., 45, 908-33.
    • (2012) Pattern Recognit. , vol.45 , pp. 908-933
    • Zollanvari, A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.