메뉴 건너뛰기




Volumn 22, Issue 2, 2009, Pages 271-282

Analysis of DNA microarray expression data

Author keywords

bioinformatics; biomarkers; gene expression signatures; microarray data analysis

Indexed keywords

ANALYTIC METHOD; ARTICLE; BIOINFORMATICS; CLASSIFIER; CLINICAL RESEARCH; DATA ANALYSIS; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETIC IDENTIFICATION; MATHEMATICAL COMPUTING; PATIENT IDENTIFICATION; PREDICTION; PRIORITY JOURNAL; PROGNOSIS; REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION; STATISTICAL ANALYSIS; SYSTEMATIC ERROR; VALIDATION PROCESS;

EID: 68749118357     PISSN: 15216926     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.beha.2009.07.001     Document Type: Article
Times cited : (43)

References (63)
  • 1
    • 33846978784 scopus 로고    scopus 로고
    • Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting
    • Dupuy A., and Simon R. Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting. J Natl Cancer Inst 99 (2007) 147-157
    • (2007) J Natl Cancer Inst , vol.99 , pp. 147-157
    • Dupuy, A.1    Simon, R.2
  • 2
    • 34447560961 scopus 로고    scopus 로고
    • Analysis of gene expression data using BRB-ArrayTools
    • Simon R., Lam A., Li M.C., et al. Analysis of gene expression data using BRB-ArrayTools. Cancer Inform 2 (2007) 11-17
    • (2007) Cancer Inform , vol.2 , pp. 11-17
    • Simon, R.1    Lam, A.2    Li, M.C.3
  • 3
    • 33645326509 scopus 로고    scopus 로고
    • Comparison of Affymetrix GeneChip expression measures
    • Irizarry R.A., Wu Z., and Jaffee H.A. Comparison of Affymetrix GeneChip expression measures. Bioinformatics 22 7 (2006) 789-794
    • (2006) Bioinformatics , vol.22 , Issue.7 , pp. 789-794
    • Irizarry, R.A.1    Wu, Z.2    Jaffee, H.A.3
  • 4
    • 0037316303 scopus 로고    scopus 로고
    • A comparison of normalization methods for high density oligonucleotide array data based on variance and bias
    • Bolstad B.M., Irizarry R.A., Astrand M., et al. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19 (2003) 185-193
    • (2003) Bioinformatics , vol.19 , pp. 185-193
    • Bolstad, B.M.1    Irizarry, R.A.2    Astrand, M.3
  • 5
    • 0642309738 scopus 로고    scopus 로고
    • Evaluation of normalization methods for microarray data
    • Park T., Yi S.G., Kang S.H., et al. Evaluation of normalization methods for microarray data. BMC Bioinformatics 4 (2003) 33
    • (2003) BMC Bioinformatics , vol.4 , pp. 33
    • Park, T.1    Yi, S.G.2    Kang, S.H.3
  • 6
    • 0037245343 scopus 로고    scopus 로고
    • Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification
    • Simon R., Radmacher M.D., Dobbin K., et al. Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. J Natl Cancer Inst 95 (2003) 14-18
    • (2003) J Natl Cancer Inst , vol.95 , pp. 14-18
    • Simon, R.1    Radmacher, M.D.2    Dobbin, K.3
  • 8
    • 0037041631 scopus 로고    scopus 로고
    • Identifying pre-post chemotherapy differences in gene expression in breast tumors: a statistical method appropriate for this aim
    • Korn E.L., McShane L.M., Troendle J.F., et al. Identifying pre-post chemotherapy differences in gene expression in breast tumors: a statistical method appropriate for this aim. Br J Cancer 86 (2002) 1093-1096
    • (2002) Br J Cancer , vol.86 , pp. 1093-1096
    • Korn, E.L.1    McShane, L.M.2    Troendle, J.F.3
  • 9
    • 24344444819 scopus 로고    scopus 로고
    • Gene expression patterns and profile changes pre- and post-erlotinib treatment in patients with metastatic breast cancer
    • Yang S.X., Simon R.M., Tan A.R., et al. Gene expression patterns and profile changes pre- and post-erlotinib treatment in patients with metastatic breast cancer. Clin Cancer Res 11 (2005) 6226-6232
    • (2005) Clin Cancer Res , vol.11 , pp. 6226-6232
    • Yang, S.X.1    Simon, R.M.2    Tan, A.R.3
  • 10
    • 0042838307 scopus 로고    scopus 로고
    • Breast cancer classification and prognosis based on gene expression profiles from a population based study
    • Sotiriou C., Neo S.Y., McShane L.M., et al. Breast cancer classification and prognosis based on gene expression profiles from a population based study. Proc Natl Acad Sci U S A 100 18 (2003) 10393-10398
    • (2003) Proc Natl Acad Sci U S A , vol.100 , Issue.18 , pp. 10393-10398
    • Sotiriou, C.1    Neo, S.Y.2    McShane, L.M.3
  • 11
    • 0037076342 scopus 로고    scopus 로고
    • Initiating oncogenic event determines gene-expression patterns of human breast cancer models
    • Desai K.V., Xiao N., Wang W., et al. Initiating oncogenic event determines gene-expression patterns of human breast cancer models. Proc Natl Acad Sci USA 99 (2002) 6967-6972
    • (2002) Proc Natl Acad Sci USA , vol.99 , pp. 6967-6972
    • Desai, K.V.1    Xiao, N.2    Wang, W.3
  • 12
    • 21444445077 scopus 로고    scopus 로고
    • Development and validation of therapeutically relevant multi-gene biomarker classifiers
    • Simon R. Development and validation of therapeutically relevant multi-gene biomarker classifiers. J Natl Cancer Inst 97 (2005) 866-867
    • (2005) J Natl Cancer Inst , vol.97 , pp. 866-867
    • Simon, R.1
  • 13
    • 18244409687 scopus 로고    scopus 로고
    • Gene expression profiling predicts clinical outcome of breast cancer
    • van'tVeer L.J., Dai H., Vijver M., et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 415 (2002) 530-536
    • (2002) Nature , vol.415 , pp. 530-536
    • van'tVeer, L.J.1    Dai, H.2    Vijver, M.3
  • 14
    • 0037137519 scopus 로고    scopus 로고
    • A gene expression signature as a predictor of survival in breast cancer
    • van-de-Vijver M.J., He Y.D., Veer L., et al. A gene expression signature as a predictor of survival in breast cancer. N Engl J Med 347 25 (2002) 1999-2009
    • (2002) N Engl J Med , vol.347 , Issue.25 , pp. 1999-2009
    • van-de-Vijver, M.J.1    He, Y.D.2    Veer, L.3
  • 15
    • 2942578063 scopus 로고    scopus 로고
    • A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen
    • Ma X.J., Wang Z., Ryan P.D., et al. A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell 5 (2004) 1-10
    • (2004) Cancer Cell , vol.5 , pp. 1-10
    • Ma, X.J.1    Wang, Z.2    Ryan, P.D.3
  • 16
    • 2942729848 scopus 로고    scopus 로고
    • Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin and cyclophosphamide chemotherapy in breast cancer
    • Ayers M., Symmans W.F., Stec J., et al. Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin and cyclophosphamide chemotherapy in breast cancer. J Clin Oncol 22 12 (2005) 2284-2293
    • (2005) J Clin Oncol , vol.22 , Issue.12 , pp. 2284-2293
    • Ayers, M.1    Symmans, W.F.2    Stec, J.3
  • 17
    • 20044377912 scopus 로고    scopus 로고
    • Molecular classification of tamoxifen-resistant breast carcinomas by gene expression profiling
    • Jansen M.P.H.M., Foekens J.A., Staveren I., et al. Molecular classification of tamoxifen-resistant breast carcinomas by gene expression profiling. J Clin Oncol 23 4 (2005) 732-740
    • (2005) J Clin Oncol , vol.23 , Issue.4 , pp. 732-740
    • Jansen, M.P.H.M.1    Foekens, J.A.2    Staveren, I.3
  • 18
    • 0034680102 scopus 로고    scopus 로고
    • Molecular portraits of human breast tumors
    • Perou C.M., Serlie T., Eisen M.B., et al. Molecular portraits of human breast tumors. Nature 406 (2000) 747-752
    • (2000) Nature , vol.406 , pp. 747-752
    • Perou, C.M.1    Serlie, T.2    Eisen, M.B.3
  • 19
    • 0036856374 scopus 로고    scopus 로고
    • Methods of assessing reproducibility of clustering patterns observed in analyses of microarray data
    • McShane L.M., Radmacher M.D., Freidlin B., et al. Methods of assessing reproducibility of clustering patterns observed in analyses of microarray data. Bioinformatics 18 (2002) 1462-1469
    • (2002) Bioinformatics , vol.18 , pp. 1462-1469
    • McShane, L.M.1    Radmacher, M.D.2    Freidlin, B.3
  • 20
    • 34248147918 scopus 로고    scopus 로고
    • Is there an alternative to increasing the sample size in microarray studies?
    • Klebanov L., and Yakovlev A. Is there an alternative to increasing the sample size in microarray studies?. Bioinformation 1 10 (2007) 429-431
    • (2007) Bioinformation , vol.1 , Issue.10 , pp. 429-431
    • Klebanov, L.1    Yakovlev, A.2
  • 21
    • 12344333513 scopus 로고    scopus 로고
    • Effects of pooling mRNA in microarray class comparison
    • Shih J.H., Michalowska A.M., Dobbin K., et al. Effects of pooling mRNA in microarray class comparison. Bioinformatics 20 (2004) 3318-3325
    • (2004) Bioinformatics , vol.20 , pp. 3318-3325
    • Shih, J.H.1    Michalowska, A.M.2    Dobbin, K.3
  • 22
    • 0141506137 scopus 로고    scopus 로고
    • Questions and answers on design of dual-label microarrays for identifying differentially expressed genes
    • Dobbin K., Shih J., and Simon R. Questions and answers on design of dual-label microarrays for identifying differentially expressed genes. J Natl Cancer Inst 95 (2003) 1362-1369
    • (2003) J Natl Cancer Inst , vol.95 , pp. 1362-1369
    • Dobbin, K.1    Shih, J.2    Simon, R.3
  • 23
    • 19544383638 scopus 로고    scopus 로고
    • Sample size determination in microarray experiments for class comparison and prognostic classification
    • Dobbin K., and Simon R. Sample size determination in microarray experiments for class comparison and prognostic classification. Biostatistics 6 (2005) 27-38
    • (2005) Biostatistics , vol.6 , pp. 27-38
    • Dobbin, K.1    Simon, R.2
  • 24
    • 33845404310 scopus 로고    scopus 로고
    • Sample size planning for developing classifiers using high dimensional DNA expression data
    • Dobbin K., and Simon R. Sample size planning for developing classifiers using high dimensional DNA expression data. Biostatistics 8 (2007) 101-117
    • (2007) Biostatistics , vol.8 , pp. 101-117
    • Dobbin, K.1    Simon, R.2
  • 25
    • 0348143180 scopus 로고    scopus 로고
    • A random variance model for detection of differential gene expression in small microarray experiments
    • Wright G.W., and Simon R. A random variance model for detection of differential gene expression in small microarray experiments. Bioinformatics 19 (2003) 2448-2455
    • (2003) Bioinformatics , vol.19 , pp. 2448-2455
    • Wright, G.W.1    Simon, R.2
  • 26
    • 0034948896 scopus 로고    scopus 로고
    • A Bayesian framework for the analysis of microarray expression data: regularized t test and statistical inferences of gene changes
    • Baldi P., and Long A.D. A Bayesian framework for the analysis of microarray expression data: regularized t test and statistical inferences of gene changes. Bioinformatics 17 (2001) 509-519
    • (2001) Bioinformatics , vol.17 , pp. 509-519
    • Baldi, P.1    Long, A.D.2
  • 27
    • 0001677717 scopus 로고
    • Controlling the false discovery rate: a practical and powerful approach to multiple testing
    • Benjamini Y., and Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B 57 (1995) 289-300
    • (1995) J R Stat Soc Series B , vol.57 , pp. 289-300
    • Benjamini, Y.1    Hochberg, Y.2
  • 28
    • 3042552023 scopus 로고    scopus 로고
    • Controlling the number of false discoveries: application to high-dimensional genomic data
    • Korn E., Troendle J.F., McShane L.M., et al. Controlling the number of false discoveries: application to high-dimensional genomic data. J Stat Plan Inference 124 (2004) 379-398
    • (2004) J Stat Plan Inference , vol.124 , pp. 379-398
    • Korn, E.1    Troendle, J.F.2    McShane, L.M.3
  • 29
    • 35148878081 scopus 로고    scopus 로고
    • An investigation of SAM and the multivariate permutation test for controlling the false discovery proportion
    • Korn E.L., Li M.C., McShane L.M., et al. An investigation of SAM and the multivariate permutation test for controlling the false discovery proportion. Statistics in Medicine 26 (2007) 4428-4440
    • (2007) Statistics in Medicine , vol.26 , pp. 4428-4440
    • Korn, E.L.1    Li, M.C.2    McShane, L.M.3
  • 30
    • 27344435774 scopus 로고    scopus 로고
    • Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles
    • Subramanian A., Tamayo P., and Mootha V.K. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102 43 (2005) 15545-15550
    • (2005) Proc Natl Acad Sci U S A , vol.102 , Issue.43 , pp. 15545-15550
    • Subramanian, A.1    Tamayo, P.2    Mootha, V.K.3
  • 31
    • 26444608611 scopus 로고    scopus 로고
    • Discovering statistically significant pathways in expression profiling studies
    • Tian L., Greenberg S.A., Kong S.W., et al. Discovering statistically significant pathways in expression profiling studies. Proc Natl Acad Sci U S A 102 38 (2005) 13544-13549
    • (2005) Proc Natl Acad Sci U S A , vol.102 , Issue.38 , pp. 13544-13549
    • Tian, L.1    Greenberg, S.A.2    Kong, S.W.3
  • 32
    • 37549017682 scopus 로고    scopus 로고
    • Gene sets expression comparison in BRB-ArrayTools
    • Xu X., Zhao Y., and Simon R. Gene sets expression comparison in BRB-ArrayTools. Bioinformatics 24 (2008) 137-139
    • (2008) Bioinformatics , vol.24 , pp. 137-139
    • Xu, X.1    Zhao, Y.2    Simon, R.3
  • 33
    • 24644519314 scopus 로고    scopus 로고
    • Significance analysis of time course microarray experiments
    • Storey J.D., Xiao W., Leek J.T., et al. Significance analysis of time course microarray experiments. Proc Natl Acad Sci U S A 102 (2005) 12837-12842
    • (2005) Proc Natl Acad Sci U S A , vol.102 , pp. 12837-12842
    • Storey, J.D.1    Xiao, W.2    Leek, J.T.3
  • 34
    • 32544433476 scopus 로고    scopus 로고
    • EDGE: extraction and analysis of differential gene expression
    • Leek J.T., Monsen E., Dabney A.R., et al. EDGE: extraction and analysis of differential gene expression. Bioinformatics 22 (2006) 507-508
    • (2006) Bioinformatics , vol.22 , pp. 507-508
    • Leek, J.T.1    Monsen, E.2    Dabney, A.R.3
  • 35
    • 18944384502 scopus 로고    scopus 로고
    • When is a genomic classifier ready for prime time?
    • Simon R. When is a genomic classifier ready for prime time?. Nat Clin Pract Oncol 1 1 (2004) 2-3
    • (2004) Nat Clin Pract Oncol , vol.1 , Issue.1 , pp. 2-3
    • Simon, R.1
  • 36
    • 0035991757 scopus 로고    scopus 로고
    • A paradigm for class prediction using gene expression profiles
    • Radmacher M.D., McShane L.M., and Simon R. A paradigm for class prediction using gene expression profiles. J Comput Biol 9 (2002) 505-512
    • (2002) J Comput Biol , vol.9 , pp. 505-512
    • Radmacher, M.D.1    McShane, L.M.2    Simon, R.3
  • 37
    • 3342964832 scopus 로고    scopus 로고
    • Classification in microarray experiments
    • Speed T. (Ed), Chapman & Hall/CRC, London, New York, Washington D.C.: Boca Raton;
    • Dudoit S., and Fridlyand J. Classification in microarray experiments. In: Speed T. (Ed). Statistical analysis of gene expression microarray data (2003), Chapman & Hall/CRC, London, New York, Washington D.C.: Boca Raton;
    • (2003) Statistical analysis of gene expression microarray data
    • Dudoit, S.1    Fridlyand, J.2
  • 38
    • 0036489046 scopus 로고    scopus 로고
    • Comparison of discrimination methods for the classification of tumors using gene expression data
    • Dudoit S., Fridlyand J., and Speed T.P. Comparison of discrimination methods for the classification of tumors using gene expression data. J Am Stat Assoc 97 (2002) 77-87
    • (2002) J Am Stat Assoc , vol.97 , pp. 77-87
    • Dudoit, S.1    Fridlyand, J.2    Speed, T.P.3
  • 39
    • 0033569406 scopus 로고    scopus 로고
    • Molecular classification of cancer: class discovery and class prediction by gene expression monitoring
    • Golub T.R., Slonim D.K., Tamayo P., et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286 (1999) 531-537
    • (1999) Science , vol.286 , pp. 531-537
    • Golub, T.R.1    Slonim, D.K.2    Tamayo, P.3
  • 40
    • 0347201147 scopus 로고    scopus 로고
    • Multiclass cancer diagnosis using tumor gene expression signatures
    • Ramaswamy S., Tamayo P., Rifkin R., et al. Multiclass cancer diagnosis using tumor gene expression signatures. Proc Natl Acad Sci U S A 98 (2001) 15149-15154
    • (2001) Proc Natl Acad Sci U S A , vol.98 , pp. 15149-15154
    • Ramaswamy, S.1    Tamayo, P.2    Rifkin, R.3
  • 41
    • 0033692876 scopus 로고    scopus 로고
    • Tissue classification with gene expression profiles
    • Ben-Dor A., Bruhn L., Friedman N., et al. Tissue classification with gene expression profiles. J Comput Biol 7 (2000) 559-584
    • (2000) J Comput Biol , vol.7 , pp. 559-584
    • Ben-Dor, A.1    Bruhn, L.2    Friedman, N.3
  • 42
    • 0037076272 scopus 로고    scopus 로고
    • Diagnosis of multiple cancer types by shrunken centroids of gene expression
    • Tibshirani R., Hastie T., Narasimhan B., et al. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci U S A 99 (2002) 6567-6572
    • (2002) Proc Natl Acad Sci U S A , vol.99 , pp. 6567-6572
    • Tibshirani, R.1    Hastie, T.2    Narasimhan, B.3
  • 43
    • 0036372855 scopus 로고    scopus 로고
    • New feature subset selection procedures for classification of expression profiles
    • Bo T.H., and Jonassen I. New feature subset selection procedures for classification of expression profiles. Genome Biol 3 4 (2002) 0017.1-0017.11
    • (2002) Genome Biol , vol.3 , Issue.4
    • Bo, T.H.1    Jonassen, I.2
  • 44
    • 0037245772 scopus 로고    scopus 로고
    • Genetic algorithms applied to multi-class prediction for the analysis of gene expression data
    • Ooi C.H., and Tan P. Genetic algorithms applied to multi-class prediction for the analysis of gene expression data. Bioinformatics 19 (2003) 37-44
    • (2003) Bioinformatics , vol.19 , pp. 37-44
    • Ooi, C.H.1    Tan, P.2
  • 45
    • 0037255041 scopus 로고    scopus 로고
    • Evolutionary algorithms for finding optimal gene sets in microarray prediction
    • Deutsch J.M. Evolutionary algorithms for finding optimal gene sets in microarray prediction. Bioinformatics 19 (2003) 45-54
    • (2003) Bioinformatics , vol.19 , pp. 45-54
    • Deutsch, J.M.1
  • 46
    • 0036211375 scopus 로고    scopus 로고
    • Strong feature sets from small samples
    • Kim S., Dougherty E.R., Barrera J., et al. Strong feature sets from small samples. J Comput Biol 9 (2002) 127-146
    • (2002) J Comput Biol , vol.9 , pp. 127-146
    • Kim, S.1    Dougherty, E.R.2    Barrera, J.3
  • 47
    • 33748961513 scopus 로고    scopus 로고
    • A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets
    • Lai C., Reinders M.J.T., Veer L., et al. A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets. BMC Bioinformatics 7 (2006) 235
    • (2006) BMC Bioinformatics , vol.7 , pp. 235
    • Lai, C.1    Reinders, M.J.T.2    Veer, L.3
  • 48
    • 33750623605 scopus 로고    scopus 로고
    • An empirical study of univariate and genetic algorithm-based feature selection in binary classification with microarray data
    • Lecocke M., and Hess K. An empirical study of univariate and genetic algorithm-based feature selection in binary classification with microarray data. Cancer Inform 2 (2006) 313-327
    • (2006) Cancer Inform , vol.2 , pp. 313-327
    • Lecocke, M.1    Hess, K.2
  • 49
    • 19944429996 scopus 로고    scopus 로고
    • Inter-laboratory comparability study of cancer gene expression analysis using oligonucleotide microarrays
    • Dobbin K., Beer D.G., Meyerson M., et al. Inter-laboratory comparability study of cancer gene expression analysis using oligonucleotide microarrays. Clin Cancer Res 11 (2005) 565-572
    • (2005) Clin Cancer Res , vol.11 , pp. 565-572
    • Dobbin, K.1    Beer, D.G.2    Meyerson, M.3
  • 50
    • 19944422061 scopus 로고    scopus 로고
    • A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer
    • Paik S., Shak S., Tang G., et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351 (2004) 2817-2826
    • (2004) N Engl J Med , vol.351 , pp. 2817-2826
    • Paik, S.1    Shak, S.2    Tang, G.3
  • 51
    • 0037142053 scopus 로고    scopus 로고
    • The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma
    • Rosenwald A., Wright G., Chan W.C., et al. The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N Engl J Med 346 (2002) 1937-1947
    • (2002) N Engl J Med , vol.346 , pp. 1937-1947
    • Rosenwald, A.1    Wright, G.2    Chan, W.C.3
  • 52
    • 13444249852 scopus 로고    scopus 로고
    • Prediction of cancer outcome with microarrays: a multiple validation strategy
    • Michiels S., Koscielny S., and Hill C. Prediction of cancer outcome with microarrays: a multiple validation strategy. Lancet 365 (2005) 488-492
    • (2005) Lancet , vol.365 , pp. 488-492
    • Michiels, S.1    Koscielny, S.2    Hill, C.3
  • 53
    • 25144494760 scopus 로고    scopus 로고
    • Prediction error estimation: a comparison of resampling methods
    • Molinaro A.M., Simon R., and Pfeiffer R.M. Prediction error estimation: a comparison of resampling methods. Bioinformatics 21 15 (2005) 3301-3307
    • (2005) Bioinformatics , vol.21 , Issue.15 , pp. 3301-3307
    • Molinaro, A.M.1    Simon, R.2    Pfeiffer, R.M.3
  • 54
    • 0028318390 scopus 로고
    • Statistical aspects of prognostic factor studies in oncology
    • Simon R., and Altman D.G. Statistical aspects of prognostic factor studies in oncology. Br J Cancer 69 (1994) 979-985
    • (1994) Br J Cancer , vol.69 , pp. 979-985
    • Simon, R.1    Altman, D.G.2
  • 55
    • 0035868668 scopus 로고    scopus 로고
    • 2000 update of recommendations for the use of tumor markers in breast and colorectal cancer: clinical practice guidelines of the American Society of Clinical Oncology
    • Bast R.C., Ravdin P., Hayes D.F., et al. 2000 update of recommendations for the use of tumor markers in breast and colorectal cancer: clinical practice guidelines of the American Society of Clinical Oncology. J Clin Oncol 19 (2001) 1865-1878
    • (2001) J Clin Oncol , vol.19 , pp. 1865-1878
    • Bast, R.C.1    Ravdin, P.2    Hayes, D.F.3
  • 56
    • 18244409933 scopus 로고    scopus 로고
    • Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning
    • Shipp M.A., Ross K.N., Tamayo P., et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat Med 8 (2002) 68-74
    • (2002) Nat Med , vol.8 , pp. 68-74
    • Shipp, M.A.1    Ross, K.N.2    Tamayo, P.3
  • 57
    • 33644688970 scopus 로고    scopus 로고
    • A roadmap for developing and validating therapeutically relevant genomic classifiers
    • Simon R. A roadmap for developing and validating therapeutically relevant genomic classifiers. J Clin Oncol 23 (2005) 7332-7341
    • (2005) J Clin Oncol , vol.23 , pp. 7332-7341
    • Simon, R.1
  • 58
    • 6044278144 scopus 로고    scopus 로고
    • Evaluating the efficiency of targeted designs for randomized clinical trials
    • Simon R., and Maitournam A. Evaluating the efficiency of targeted designs for randomized clinical trials. Clin Cancer Res 10 (2005) 6759-6763
    • (2005) Clin Cancer Res , vol.10 , pp. 6759-6763
    • Simon, R.1    Maitournam, A.2
  • 59
    • 58149151278 scopus 로고    scopus 로고
    • Using genomics in clinical trial design
    • Simon R. Using genomics in clinical trial design. Clin Cancer Res 14 (2008) 5984-5993
    • (2008) Clin Cancer Res , vol.14 , pp. 5984-5993
    • Simon, R.1
  • 60
    • 15744374441 scopus 로고    scopus 로고
    • Clinical trial designs for predictive marker validation in cancer treatment trials
    • Sargent D.J., Conley B.A., and Allegra C. Clinical trial designs for predictive marker validation in cancer treatment trials. J Clin Oncol 23 9 (2005) 2020-2027
    • (2005) J Clin Oncol , vol.23 , Issue.9 , pp. 2020-2027
    • Sargent, D.J.1    Conley, B.A.2    Allegra, C.3
  • 61
    • 10944260135 scopus 로고    scopus 로고
    • Clinical trial design for microarray predictive marker discovery and assessment
    • Pusztai L., and Hess K.R. Clinical trial design for microarray predictive marker discovery and assessment. Ann Oncol 15 (2004) 1731-1737
    • (2004) Ann Oncol , vol.15 , pp. 1731-1737
    • Pusztai, L.1    Hess, K.R.2
  • 62
    • 33750601244 scopus 로고    scopus 로고
    • Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial
    • Bogaerts J., Cardoso F., Buyse M., et al. Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nat Clin Pract Oncol 3 10 (2006) 540-551
    • (2006) Nat Clin Pract Oncol , vol.3 , Issue.10 , pp. 540-551
    • Bogaerts, J.1    Cardoso, F.2    Buyse, M.3
  • 63
    • 33646047815 scopus 로고    scopus 로고
    • Use of genomic signatures in therapeutics development
    • Simon R., and Wang S.J. Use of genomic signatures in therapeutics development. Pharmacogenomics J 6 (2006) 166-173
    • (2006) Pharmacogenomics J , vol.6 , pp. 166-173
    • Simon, R.1    Wang, S.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.