메뉴 건너뛰기




Volumn 13, Issue 3, 2009, Pages 219-237

Unsupervised selection of highly coexpressed and noncoexpressed genes using a consensus clustering approach

Author keywords

[No Author keywords available]

Indexed keywords

ENDOTOXIN;

EID: 67651165147     PISSN: 15362310     EISSN: None     Source Type: Journal    
DOI: 10.1089/omi.2008.0074     Document Type: Article
Times cited : (23)

References (68)
  • 1
    • 35348872479 scopus 로고    scopus 로고
    • Analysis of time-series gene expression data: Methods, challenges, and opportunities
    • Androulakis, I.P., Yang, E., and Almon, R.R. (2007). Analysis of time-series gene expression data: methods, challenges, and opportunities. Annu Rev Biomed Eng 9, 205-228.
    • (2007) Annu Rev Biomed Eng , vol.9 , pp. 205-228
    • Androulakis, I.P.1    Yang, E.2    Almon, R.R.3
  • 2
    • 33846606051 scopus 로고    scopus 로고
    • Clustering methods for microarray gene expression data
    • Belacel, N., Wang, Q., and Cuperlovic-Culf, M. (2006). Clustering methods for microarray gene expression data. OMICS 10, 507-531.
    • (2006) OMICS , vol.10 , pp. 507-531
    • Belacel, N.1    Wang, Q.2    Cuperlovic-Culf, M.3
  • 3
    • 33646825842 scopus 로고    scopus 로고
    • Estimating the number of clusters in DNA microarray data
    • Bolshakova, N., and Azuaje, F. (2006). Estimating the number of clusters in DNA microarray data. Methods Inf Med 45, 153-157.
    • (2006) Methods Inf Med , vol.45 , pp. 153-157
    • Bolshakova, N.1    Azuaje, F.2
  • 5
    • 34249707214 scopus 로고    scopus 로고
    • Nuclear factor-kappaB: Activation and regulation during toll-like receptor signaling
    • Carmody, R.J., and Chen, Y.H. (2007). Nuclear factor-kappaB: activation and regulation during toll-like receptor signaling. Cell Mol Immunol 4, 31-41.
    • (2007) Cell Mol Immunol , vol.4 , pp. 31-41
    • Carmody, R.J.1    Chen, Y.H.2
  • 6
    • 33645579248 scopus 로고    scopus 로고
    • Hybrid hierarchical clustering with applications to microarray data
    • Chipman, H., and Tibshirani, R. (2006). Hybrid hierarchical clustering with applications to microarray data. Biostatistics 7, 286-301.
    • (2006) Biostatistics , vol.7 , pp. 286-301
    • Chipman, H.1    Tibshirani, R.2
  • 7
    • 0033574415 scopus 로고    scopus 로고
    • Toll-like receptor-4 mediates lipopolysaccharide- induced signal transduction
    • Chow, J.C., Young, D.W., Golenbock, D.T., Christ, W.J., and Gusovsky, F. (1999). Toll-like receptor-4 mediates lipopolysaccharide- induced signal transduction. J Biol Chem 274, 10689-10692.
    • (1999) J Biol Chem , vol.274 , pp. 10689-10692
    • Chow, J.C.1    Young, D.W.2    Golenbock, D.T.3    Christ, W.J.4    Gusovsky, F.5
  • 8
    • 0032561246 scopus 로고    scopus 로고
    • The transcriptional program of sporulation in budding yeast
    • Chu, S., Derisi, J., Eisen, M., Mulholland, J., Botstein, D., Brown, P.O., et al. (1998). The transcriptional program of sporulation in budding yeast. Science 282, 699-705.
    • (1998) Science , vol.282 , pp. 699-705
    • Chu, S.1    Derisi, J.2    Eisen, M.3    Mulholland, J.4    Botstein, D.5    Brown, P.O.6
  • 9
    • 33646080342 scopus 로고    scopus 로고
    • Residual closeness in networks
    • Dangalchev, C. (2006). Residual closeness in networks. Physica A 365, 556-564.
    • (2006) Physica A , vol.365 , pp. 556-564
    • Dangalchev, C.1
  • 10
    • 30644464444 scopus 로고    scopus 로고
    • Gene selection and classification of microarray data using random forest
    • Diaz-Uriarte, R., and Alvarez de Andres, S. (2006). Gene selection and classification of microarray data using random forest. BMC Bioinformatics 7, 3.
    • (2006) BMC Bioinformatics , vol.7 , pp. 3
    • Diaz-Uriarte, R.1    Alvarez de Andres, S.2
  • 11
    • 67651159783 scopus 로고    scopus 로고
    • Dimitriadou, E., Hornik, K., Leisch, F., Meyer, D., and Weingessel, A. (2006). e1071: Misc Functions of the Department of Statistics. R packages.
    • Dimitriadou, E., Hornik, K., Leisch, F., Meyer, D., and Weingessel, A. (2006). e1071: Misc Functions of the Department of Statistics. R packages.
  • 12
    • 0038494599 scopus 로고    scopus 로고
    • Unsupervised feature selection via two-way ordering in gene expression analysis
    • Ding, C.H. (2003). Unsupervised feature selection via two-way ordering in gene expression analysis. Bioinformatics 19, 1259-1266.
    • (2003) Bioinformatics , vol.19 , pp. 1259-1266
    • Ding, C.H.1
  • 13
    • 0037172724 scopus 로고    scopus 로고
    • A prediction-based resampling method for estimating the number of clusters in a dataset
    • RESEARCH0036
    • Dudoit, S., and Fridlyand, J. (2002). A prediction-based resampling method for estimating the number of clusters in a dataset. Genome Biol 3, RESEARCH0036.
    • (2002) Genome Biol , vol.3
    • Dudoit, S.1    Fridlyand, J.2
  • 14
    • 0032441150 scopus 로고    scopus 로고
    • Cluster analysis and display of genome-wide expression patterns
    • Eisen, M.B., Spellman, P.T., Brown, P.O., and Botstein, D. (1998). Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 95, 14863-14868.
    • (1998) Proc Natl Acad Sci USA , vol.95 , pp. 14863-14868
    • Eisen, M.B.1    Spellman, P.T.2    Brown, P.O.3    Botstein, D.4
  • 15
    • 3242783231 scopus 로고    scopus 로고
    • Clusterability detection and initial seed selection in large datasets
    • Technical report, Rensselaer Polytechnic Institute
    • Epter, S., Krisnamoothy, M., and Zaki, M. (1999). Clusterability detection and initial seed selection in large datasets. Technical report, Rensselaer Polytechnic Institute.
    • (1999)
    • Epter, S.1    Krisnamoothy, M.2    Zaki, M.3
  • 16
    • 0000550189 scopus 로고    scopus 로고
    • A density- based algorithm for discovering clusters in large spatial databases with noise
    • AAAI Press, Menlo Park, pp
    • Ester, M., Krisnamoothy, H., Sander, J., and Xu, X. (1996). A density- based algorithm for discovering clusters in large spatial databases with noise. Proc. KDD' 96, AAAI Press, Menlo Park, pp. 226-231.
    • (1996) Proc. KDD' 96 , pp. 226-231
    • Ester, M.1    Krisnamoothy, H.2    Sander, J.3    Xu, X.4
  • 17
    • 33645281761 scopus 로고    scopus 로고
    • Knowledge guided analysis of microarray data
    • Fang, Z., Yang, J., Li, Y., Luo, Q., and Liu, L. (2006). Knowledge guided analysis of microarray data. J Biomed Inform 39, 401-411.
    • (2006) J Biomed Inform , vol.39 , pp. 401-411
    • Fang, Z.1    Yang, J.2    Li, Y.3    Luo, Q.4    Liu, L.5
  • 18
    • 35348936633 scopus 로고    scopus 로고
    • Gene regulation: The many paths to coexpression
    • Flintoft, L. (2007). Gene regulation: The many paths to coexpression. Nat Rev Genet 8, 827.
    • (2007) Nat Rev Genet , vol.8 , pp. 827
    • Flintoft, L.1
  • 20
    • 0000673504 scopus 로고
    • Multivariate generalization of the Wald-Wolfowitz and Smirnov two-sample tests
    • Friedman, J.H., and Rafsky, L.C. (1979). Multivariate generalization of the Wald-Wolfowitz and Smirnov two-sample tests. Ann Statist 7, 697-717.
    • (1979) Ann Statist , vol.7 , pp. 697-717
    • Friedman, J.H.1    Rafsky, L.C.2
  • 21
    • 67651155217 scopus 로고    scopus 로고
    • Gentleman, R.C, Carey, V, and Huber, W. genefilter: methods for filtering genes from microarray experiments. R packages
    • Gentleman, R.C., Carey, V., and Huber, W. genefilter: methods for filtering genes from microarray experiments. R packages.
  • 23
    • 0036798238 scopus 로고    scopus 로고
    • Judging the quality of gene expression-based clustering methods using gene annotation
    • Gibbons, F.D., and Roth, F.P. (2002). Judging the quality of gene expression-based clustering methods using gene annotation. Genome Res 12, 1574-1581.
    • (2002) Genome Res , vol.12 , pp. 1574-1581
    • Gibbons, F.D.1    Roth, F.P.2
  • 24
    • 30344442460 scopus 로고    scopus 로고
    • Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm
    • Grotkjaer, T., Winther, O., Regenberg, B., Nielsen, J., and Hansen, L.K. (2006). Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm. Bioinformatics 22, 58-67.
    • (2006) Bioinformatics , vol.22 , pp. 58-67
    • Grotkjaer, T.1    Winther, O.2    Regenberg, B.3    Nielsen, J.4    Hansen, L.K.5
  • 25
    • 37049024068 scopus 로고    scopus 로고
    • Optimal search space for clustering gene expression data via consensus
    • Hirsch, M., Swift, S., and Liu, X. (2007). Optimal search space for clustering gene expression data via consensus. J Comput Biol 14, 1327-1341.
    • (2007) J Comput Biol , vol.14 , pp. 1327-1341
    • Hirsch, M.1    Swift, S.2    Liu, X.3
  • 26
    • 33750288937 scopus 로고    scopus 로고
    • Apoptosis and caspases regulate death and inflammation in sepsis
    • Hotchkiss, R.S., and Nicholson, D.W. (2006). Apoptosis and caspases regulate death and inflammation in sepsis. Nat Rev Immunol 6, 813-822.
    • (2006) Nat Rev Immunol , vol.6 , pp. 813-822
    • Hotchkiss, R.S.1    Nicholson, D.W.2
  • 27
    • 33646895693 scopus 로고    scopus 로고
    • Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data
    • Huang, D., and Pan, W. (2006). Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data. Bioinformatics 22, 1259-1268.
    • (2006) Bioinformatics , vol.22 , pp. 1259-1268
    • Huang, D.1    Pan, W.2
  • 28
    • 11244346557 scopus 로고    scopus 로고
    • Variance stabilization applied to microarray data calibration and to the quantification of differential expression
    • Huber, W., Von Heydebreck, A., Sultmann, H., Poustka, A., and Vingron, M. (2002). Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics 18(Suppl 1), S96-S104.
    • (2002) Bioinformatics , vol.18 , Issue.SUPPL. 1
    • Huber, W.1    Von Heydebreck, A.2    Sultmann, H.3    Poustka, A.4    Vingron, M.5
  • 29
    • 0000412069 scopus 로고    scopus 로고
    • GEST: A gene expression search tool based on a novel Bayesian similarity metric
    • Hunter, L., Taylor, R.C., Leach, S.M., and Simon, R. (2001). GEST: a gene expression search tool based on a novel Bayesian similarity metric. Bioinformatics 17(Suppl 1), S115-S122.
    • (2001) Bioinformatics , vol.17 , Issue.SUPPL. 1
    • Hunter, L.1    Taylor, R.C.2    Leach, S.M.3    Simon, R.4
  • 32
    • 3042532685 scopus 로고    scopus 로고
    • Filter versus wrapper gene selection approaches in DNA microarray domains
    • Inza, I., Larranaga, P., Blanco, R., and Cerrolaza, A.J. (2004). Filter versus wrapper gene selection approaches in DNA microarray domains. Artif Intell Med 31, 91-103.
    • (2004) Artif Intell Med , vol.31 , pp. 91-103
    • Inza, I.1    Larranaga, P.2    Blanco, R.3    Cerrolaza, A.J.4
  • 33
    • 13844276694 scopus 로고    scopus 로고
    • Cluster analysis for gene expression data: A survey
    • Jiang, D., Tang, C., and Zhang, A. (2004). Cluster analysis for gene expression data: a survey. IEEE Trans Knowledge Data Eng 16, 1370-1386.
    • (2004) IEEE Trans Knowledge Data Eng , vol.16 , pp. 1370-1386
    • Jiang, D.1    Tang, C.2    Zhang, A.3
  • 34
    • 0037715342 scopus 로고    scopus 로고
    • Simultaneous gene clustering and subset selection for sample classification via MDL
    • Jornsten, R., and Yu, B. (2003). Simultaneous gene clustering and subset selection for sample classification via MDL. Bioinformatics 19, 1100-1109.
    • (2003) Bioinformatics , vol.19 , pp. 1100-1109
    • Jornsten, R.1    Yu, B.2
  • 37
    • 34247250323 scopus 로고    scopus 로고
    • Consensus framework for exploring microarray data using multiple clustering methods
    • Laderas, T., and McWeeney, S. (2007). Consensus framework for exploring microarray data using multiple clustering methods. OMICs 11, 116-128.
    • (2007) OMICs , vol.11 , pp. 116-128
    • Laderas, T.1    McWeeney, S.2
  • 38
    • 67651176908 scopus 로고    scopus 로고
    • Maechler, M., Rousseeuw, P., Struyf, A., and Hubert, M. (2005). cluster: Cluster Analysis Basics and Extensions. R packages.
    • Maechler, M., Rousseeuw, P., Struyf, A., and Hubert, M. (2005). cluster: Cluster Analysis Basics and Extensions. R packages.
  • 39
    • 0038724494 scopus 로고    scopus 로고
    • Consensus clustering: A resampling-based method for class discovery and visualization of gene expression microarray data
    • Monti, S., Tamayo, P., Mesirov, J., Golub, T. (2003). Consensus clustering: a resampling-based method for class discovery and visualization of gene expression microarray data. Mach Learn 52, 91-118.
    • (2003) Mach Learn , vol.52 , pp. 91-118
    • Monti, S.1    Tamayo, P.2    Mesirov, J.3    Golub, T.4
  • 41
    • 33847351136 scopus 로고    scopus 로고
    • The JAK-STAT signaling pathway: Input and output integration
    • Murray, P.J. (2007). The JAK-STAT signaling pathway: input and output integration. J Immunol 178, 2623-2629.
    • (2007) J Immunol , vol.178 , pp. 2623-2629
    • Murray, P.J.1
  • 42
    • 0035999977 scopus 로고    scopus 로고
    • A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments
    • Pan, W. (2002). A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments. Bioinformatics 18, 546-554.
    • (2002) Bioinformatics , vol.18 , pp. 546-554
    • Pan, W.1
  • 43
    • 33645289673 scopus 로고    scopus 로고
    • Incorporating gene functions as priors in modelbased clustering of microarray gene expression data
    • Pan, W. (2006). Incorporating gene functions as priors in modelbased clustering of microarray gene expression data. Bioinformatics 22, 795-801.
    • (2006) Bioinformatics , vol.22 , pp. 795-801
    • Pan, W.1
  • 44
    • 0242302280 scopus 로고    scopus 로고
    • Using ANOVA for gene selection from microarray studies of the nervous system
    • Pavlidis, P. (2003). Using ANOVA for gene selection from microarray studies of the nervous system. Methods 31, 282-289.
    • (2003) Methods , vol.31 , pp. 282-289
    • Pavlidis, P.1
  • 45
    • 34748847850 scopus 로고    scopus 로고
    • A Synthetic Data Generator for Clustering and Outlier Analysis
    • Technical report, University of Alberta, TR06-15
    • Pei, Y., and Zaãane, O. (2006). A Synthetic Data Generator for Clustering and Outlier Analysis. Technical report, University of Alberta, TR06-15.
    • (2006)
    • Pei, Y.1    Zaãane, O.2
  • 46
    • 0035861975 scopus 로고    scopus 로고
    • Beyond synexpression relationships: Local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions
    • Qian, J., Dolled-Filhart, M., Lin, J., Yu, H., and Gerstein, M. (2001). Beyond synexpression relationships: local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions. J Mol Biol 314, 1053-1066.
    • (2001) J Mol Biol , vol.314 , pp. 1053-1066
    • Qian, J.1    Dolled-Filhart, M.2    Lin, J.3    Yu, H.4    Gerstein, M.5
  • 47
    • 84950632109 scopus 로고
    • Objective criteria for the evaluation of clustering methods
    • Rand , W.M. (1971). Objective criteria for the evaluation of clustering methods. J Am Stat Assoc 66, 846-850.
    • (1971) J Am Stat Assoc , vol.66 , pp. 846-850
    • Rand, W.M.1
  • 48
    • 0037707302 scopus 로고    scopus 로고
    • Adaptive double self-organizing maps for clustering gene expression profiles
    • Ressom, H., Wang, D., and Natarajan, P. (2003). Adaptive double self-organizing maps for clustering gene expression profiles. Neural Netw 16, 633-640.
    • (2003) Neural Netw , vol.16 , pp. 633-640
    • Ressom, H.1    Wang, D.2    Natarajan, P.3
  • 49
    • 0034565041 scopus 로고    scopus 로고
    • CLICK: A clustering algorithm with applications to gene expression analysis
    • Sharan, R., and Shamir, R. (2000). CLICK: a clustering algorithm with applications to gene expression analysis. Proc Int Conf Intell Syst Mol Biol 8, 307-316.
    • (2000) Proc Int Conf Intell Syst Mol Biol , vol.8 , pp. 307-316
    • Sharan, R.1    Shamir, R.2
  • 50
    • 4043128084 scopus 로고    scopus 로고
    • Multiorgan failure is an adaptive, endocrine-mediated, metabolic response to overwhelming systemic inflammation
    • Singer, M., De Santis, V., Vitale, D., and Jeffcoate, W. (2004). Multiorgan failure is an adaptive, endocrine-mediated, metabolic response to overwhelming systemic inflammation. Lancet 364, 545-548.
    • (2004) Lancet , vol.364 , pp. 545-548
    • Singer, M.1    De Santis, V.2    Vitale, D.3    Jeffcoate, W.4
  • 53
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles a knowledge reuse framework for combining multiple partitions
    • Strehl, A., and Ghosh, J. (2002). Cluster ensembles a knowledge reuse framework for combining multiple partitions. J Machine Learn Res 3, 583-617.
    • (2002) J Machine Learn Res , vol.3 , pp. 583-617
    • Strehl, A.1    Ghosh, J.2
  • 54
    • 0042388208 scopus 로고    scopus 로고
    • RankGene: Identification of diagnostic genes based on expression data
    • Su, Y., Murali, T.M., Pavlovic, V., Schaffer, M., and Kasif, S. (2003). RankGene: identification of diagnostic genes based on expression data. Bioinformatics 19, 1578-1579.
    • (2003) Bioinformatics , vol.19 , pp. 1578-1579
    • Su, Y.1    Murali, T.M.2    Pavlovic, V.3    Schaffer, M.4    Kasif, S.5
  • 55
    • 24944539029 scopus 로고    scopus 로고
    • Consensus clustering and functional interpretation of gene-expression data
    • Swift, S., Tucker, A., Vinciotti, V., Martin, N., Orengo, C., Liu, X., et al. (2004). Consensus clustering and functional interpretation of gene-expression data. Genome Biol 5, R94.
    • (2004) Genome Biol , vol.5
    • Swift, S.1    Tucker, A.2    Vinciotti, V.3    Martin, N.4    Orengo, C.5    Liu, X.6
  • 56
    • 0035532141 scopus 로고    scopus 로고
    • Estimating the number of clusters in a data set via the gap statistic
    • Tibshirani, R., Walther, G., and Hastie, T. (2001). Estimating the number of clusters in a data set via the gap statistic. J R Stat Soc 63, 411-423.
    • (2001) J R Stat Soc , vol.63 , pp. 411-423
    • Tibshirani, R.1    Walther, G.2    Hastie, T.3
  • 57
    • 0346243568 scopus 로고    scopus 로고
    • ArrayTrack-supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research
    • Tong, W., Cao, X., Harris, S., Sun, H., Fang, H., Fuscoe, J., et al. (2003). ArrayTrack-supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research. Environ Health Perspect 111, 1819-1826.
    • (2003) Environ Health Perspect , vol.111 , pp. 1819-1826
    • Tong, W.1    Cao, X.2    Harris, S.3    Sun, H.4    Fang, H.5    Fuscoe, J.6
  • 58
    • 30144442247 scopus 로고    scopus 로고
    • Clustering ensembles: Models of consensus and weak partitions
    • Topchy, A., Jain, A.K., and Punch, W. (2005). Clustering ensembles: models of consensus and weak partitions. IEEE Trans Pattern Anal Mach Intell 27, 1866-1881.
    • (2005) IEEE Trans Pattern Anal Mach Intell , vol.27 , pp. 1866-1881
    • Topchy, A.1    Jain, A.K.2    Punch, W.3
  • 59
    • 0035942271 scopus 로고    scopus 로고
    • Significance analysis of microarrays applied to the ionizing radiation response
    • Tusher, V.G., Tibshirani, R., and Chu, G. (2001). Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 98, 5116-5121.
    • (2001) Proc Natl Acad Sci USA , vol.98 , pp. 5116-5121
    • Tusher, V.G.1    Tibshirani, R.2    Chu, G.3
  • 60
    • 0042384763 scopus 로고    scopus 로고
    • Hybrid clustering of gene expression data with visualization and the bootstrap
    • Van der Laan, M.J., and Pollard, K.S. (2003). Hybrid clustering of gene expression data with visualization and the bootstrap. J Stat Plann Inference 117, 275-303.
    • (2003) J Stat Plann Inference , vol.117 , pp. 275-303
    • Van der Laan, M.J.1    Pollard, K.S.2
  • 61
    • 38849091390 scopus 로고    scopus 로고
    • Hybrid huberized support vector machines for microarray classification and gene selection
    • Wang, L., Zhu, J., and Zou, H. (2008). Hybrid huberized support vector machines for microarray classification and gene selection. Bioinformatics 24, 412-419.
    • (2008) Bioinformatics , vol.24 , pp. 412-419
    • Wang, L.1    Zhu, J.2    Zou, H.3
  • 62
    • 34547649056 scopus 로고    scopus 로고
    • CoXpress: Differential co-expression in gene expression data
    • Watson, M. (2006). CoXpress: differential co-expression in gene expression data, BMC Bioinformatics 7, 509.
    • (2006) BMC Bioinformatics , vol.7 , pp. 509
    • Watson, M.1
  • 63
    • 67651152051 scopus 로고    scopus 로고
    • Yan, J. (2004). som: Self-Organizing Map. R packages.
    • Yan, J. (2004). som: Self-Organizing Map. R packages.
  • 64
    • 36749055295 scopus 로고    scopus 로고
    • Determining the number of clusters using the weighted gap statistic
    • Yan, M., and Ye, K. (2007). Determining the number of clusters using the weighted gap statistic. Biometrics 63, 1031-1037.
    • (2007) Biometrics , vol.63 , pp. 1031-1037
    • Yan, M.1    Ye, K.2
  • 65
    • 0037667290 scopus 로고    scopus 로고
    • Clustering gene-expression data with repeated measurements
    • Yeung, K.Y., Medvedovic, M., and Bumgarner, R.E. (2003). Clustering gene-expression data with repeated measurements. Genome Biol 4, R34.
    • (2003) Genome Biol , vol.4
    • Yeung, K.Y.1    Medvedovic, M.2    Bumgarner, R.E.3
  • 66
    • 34250676530 scopus 로고    scopus 로고
    • Recursive cluster elimination (RCE) for classification and feature selection from gene expression data
    • Yousef, M., Jung, S., Showe, L.C., and Showe, M.K. (2007). Recursive cluster elimination (RCE) for classification and feature selection from gene expression data. BMC Bioinformatics 8, 144.
    • (2007) BMC Bioinformatics , vol.8 , pp. 144
    • Yousef, M.1    Jung, S.2    Showe, L.C.3    Showe, M.K.4
  • 67
    • 36448947175 scopus 로고    scopus 로고
    • Graph-based consensus clustering for class discovery from gene expression data
    • Yu, Z., Wong, H.S., and Wang, H. (2007). Graph-based consensus clustering for class discovery from gene expression data. Bioinformatics 23, 2888-2896.
    • (2007) Bioinformatics , vol.23 , pp. 2888-2896
    • Yu, Z.1    Wong, H.S.2    Wang, H.3
  • 68
    • 0034334064 scopus 로고    scopus 로고
    • Assessing reliability of gene clusters from gene expression data
    • Zhang, K., and Zhao, H. (2000). Assessing reliability of gene clusters from gene expression data. Funct Integr Genomics 1, 156-173.
    • (2000) Funct Integr Genomics , vol.1 , pp. 156-173
    • Zhang, K.1    Zhao, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.