메뉴 건너뛰기




Volumn , Issue , 2007, Pages 365-383

Clustering of Microarray Data via Mixture Models

Author keywords

Agglomerative hierarchical method; Microarray data clustering; Self organizing maps (SOMs)

Indexed keywords

CLUSTERING ALGORITHMS; CONFORMAL MAPPING;

EID: 73349119261     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470181218.ch21     Document Type: Chapter
Times cited : (1)

References (62)
  • 1
    • 24944472983 scopus 로고    scopus 로고
    • Clustering on the unit hypersphere using von Mises-Fisher distributions
    • Banerjee, A., Dhillon, I. S., Ghosh, J., and Sra, S., Clustering on the unit hypersphere using von Mises-Fisher distributions, J. Machine Learn. Res. 6, 1345-1382 (2005).
    • (2005) J. Machine Learn. Res. , vol.6 , pp. 1345-1382
    • Banerjee, A.1    Dhillon, I.S.2    Ghosh, J.3    Sra, S.4
  • 2
    • 0027453616 scopus 로고
    • Model-based Gaussian and non-Gaussian clustering
    • Banfield, J. D. and Raftery, A. E. Model-based Gaussian and non-Gaussian clustering, Biometrics 49, 803-821 (1993).
    • (1993) Biometrics , vol.49 , pp. 803-821
    • Banfield, J.D.1    Raftery, A.E.2
  • 3
    • 30344471882 scopus 로고    scopus 로고
    • A generalized clustering problem, with application to DNA microarrays
    • Art. 2
    • Belitskaya-Levy, I., A generalized clustering problem, with application to DNA microarrays, Statist. Appli. Genet. Molec. Biol. 5, Art. 2, (2006).
    • (2006) Statist. Appli. Genet. Molec. Biol. , vol.5
    • Belitskaya-Levy, I.1
  • 5
    • 20444442286 scopus 로고    scopus 로고
    • Problems in gene clustering based on gene expression data
    • Bryan, J., Problems in gene clustering based on gene expression data, J. Multivar. Anal. 90, 44-66 (2004).
    • (2004) J. Multivar. Anal. , vol.90 , pp. 44-66
    • Bryan, J.1
  • 6
    • 26844458204 scopus 로고    scopus 로고
    • Mixture of linear mixed models for clustering gene expression profiles from repeated microarray experiments
    • Celeux, G., Martin, O., and Lavergne, C., Mixture of linear mixed models for clustering gene expression profiles from repeated microarray experiments, Statist. Model. 5, 243-267 (2005).
    • (2005) Statist. Model. , vol.5 , pp. 243-267
    • Celeux, G.1    Martin, O.2    Lavergne, C.3
  • 7
    • 0036940312 scopus 로고    scopus 로고
    • How well do we understand the clusters in microarray data?
    • Clare, A. and King, R. D., How well do we understand the clusters in microarray data?, In Silico Biol. 2, 511-522 (2002).
    • (2002) In Silico Biol. , vol.2 , pp. 511-522
    • Clare, A.1    King, R.D.2
  • 9
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm (with discussion)
    • Dempster, A. P., Laird, N. M., and Rubin, D. B. Maximum likelihood from incomplete data via the EM algorithm (with discussion), J. Roy. Statist. Soc. B 39, 1-38 (1977).
    • (1977) J. Roy. Statist. Soc. B , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 10
    • 0030669030 scopus 로고    scopus 로고
    • Exploring the metabolic and genetic control of gene expression on a genomic scale
    • DeRisi, J. L., Iyer, V. R., and Brown, P. O., Exploring the metabolic and genetic control of gene expression on a genomic scale, Science 278, 680-686 (1997).
    • (1997) Science , vol.278 , pp. 680-686
    • DeRisi, J.L.1    Iyer, V.R.2    Brown, P.O.3
  • 11
    • 0037172724 scopus 로고    scopus 로고
    • A prediction-based resampling method for estimating the number of clusters in a dataset
    • research
    • Dudoit, S. and Fridlyand, J., A prediction-based resampling method for estimating the number of clusters in a dataset, Genome Biol. 3, research0036.1-0036.21 (2002).
    • (2002) Genome Biol. , vol.3 , pp. 0036.1-0036.21
    • Dudoit, S.1    Fridlyand, J.2
  • 12
    • 0036376993 scopus 로고    scopus 로고
    • Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments
    • Dudoit, S., Yang, Y. H., Callow, M. J., and Speed, T. P., Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments, Statistica Sinica 12, 111-139 (2002).
    • (2002) Statistica Sinica , vol.12 , pp. 111-139
    • Dudoit, S.1    Yang, Y.H.2    Callow, M.J.3    Speed, T.P.4
  • 13
    • 0003991665 scopus 로고
    • An Introduction to the Bootstrap
    • Chapman & Hall, London
    • Efron, B. and Tibshirani, R., An Introduction to the Bootstrap, Chapman & Hall, London, 1993.
    • (1993)
    • Efron, B.1    Tibshirani, R.2
  • 14
    • 0032441150 scopus 로고    scopus 로고
    • Cluster analysis and display of genome-wide expression patterns
    • USA
    • Eisen, M. B., Spellman, P. T., Brown, P. O., and Botstein, D., Cluster analysis and display of genome-wide expression patterns, Proc. Natl. Acad. Sci. USA 95, 14863-14868 (1998).
    • (1998) Proc. Natl. Acad. Sci. , vol.95 , pp. 14863-14868
    • Eisen, M.B.1    Spellman, P.T.2    Brown, P.O.3    Botstein, D.4
  • 15
    • 0033031437 scopus 로고    scopus 로고
    • DNA Arrays for analysis of gene expression
    • Eisen, M. B. and Brown, P. O., DNA Arrays for analysis of gene expression, Meth. Enzymol. 303, 179-205 (1999).
    • (1999) Meth. Enzymol. , vol.303 , pp. 179-205
    • Eisen, M.B.1    Brown, P.O.2
  • 16
    • 0032269108 scopus 로고    scopus 로고
    • How many clusters? Which clustering method? Answers via model-based cluster analysis
    • Fraley, C. and Raftery, A. E., How many clusters? Which clustering method? Answers via model-based cluster analysis, Comput. J. 41, 578-588 (1998).
    • (1998) Comput. J. , vol.41 , pp. 578-588
    • Fraley, C.1    Raftery, A.E.2
  • 17
    • 0035998835 scopus 로고    scopus 로고
    • Model-based clustering, discriminant analysis, and density estimation
    • Fraley, C. and Raftery, A. E., Model-based clustering, discriminant analysis, and density estimation, J. Am. Statist. Assoc. 97, 611-631 (2002).
    • (2002) J. Am. Statist. Assoc. , vol.97 , pp. 611-631
    • Fraley, C.1    Raftery, A.E.2
  • 18
    • 8644255832 scopus 로고    scopus 로고
    • Clustering objects on subsets of attributes (with discussion)
    • Friedman, J. H. and Meulman, J. J., Clustering objects on subsets of attributes (with discussion), J. Roy. Statist. Soc. B 66, 815-849 (2004).
    • (2004) J. Roy. Statist. Soc. B , vol.66 , pp. 815-849
    • Friedman, J.H.1    Meulman, J.J.2
  • 19
    • 0018128173 scopus 로고
    • The efficiency of a linear discriminant function based on unclassified initial samples
    • Ganesalingam, S. and McLachlan, G. J., The efficiency of a linear discriminant function based on unclassified initial samples, Biometrika 65, 658-662 (1978).
    • (1978) Biometrika , vol.65 , pp. 658-662
    • Ganesalingam, S.1    McLachlan, G.J.2
  • 20
    • 0034710876 scopus 로고    scopus 로고
    • Coupled two-way clustering analysis of gene microarray data
    • Getz, G., Levine, E., and Domany, E., Coupled two-way clustering analysis of gene microarray data, Cell Biol. 97, 12079-12084 (2000).
    • (2000) Cell Biol. , vol.97 , pp. 12079-12084
    • Getz, G.1    Levine, E.2    Domany, E.3
  • 21
    • 0036188158 scopus 로고    scopus 로고
    • Mixture modelling of gene expression data from microarray experiments
    • Ghosh, D. and Chinnaiyan, A. M., Mixture modelling of gene expression data from microarray experiments, Bioinformatics 18, 275-286 (2002).
    • (2002) Bioinformatics , vol.18 , pp. 275-286
    • Ghosh, D.1    Chinnaiyan, A.M.2
  • 22
    • 0036798238 scopus 로고    scopus 로고
    • Judging the quality of gene expression-based clustering methods using gene annotation
    • Gibbons, F. D. and Roth, F. P., Judging the quality of gene expression-based clustering methods using gene annotation, Genome Res. 12, 1574-1581 (2002).
    • (2002) Genome Res. , vol.12 , pp. 1574-1581
    • Gibbons, F.D.1    Roth, F.P.2
  • 23
    • 27744581052 scopus 로고    scopus 로고
    • Finding groups in gene expression data
    • Hand, D. J. and Heard, N. A., Finding groups in gene expression data, J. Biomed. Biotechnol. 2005, 215-225 (2005).
    • (2005) J. Biomed. Biotechnol. , vol.2005 , pp. 215-225
    • Hand, D.J.1    Heard, N.A.2
  • 24
    • 0003445439 scopus 로고
    • Multilevel Statistical Models, 2nd ed.
    • Arnold, London
    • Goldstein, H., Multilevel Statistical Models, 2nd ed., Arnold, London, 1995.
    • (1995)
    • Goldstein, H.1
  • 25
    • 33748888529 scopus 로고
    • Statistical theory in clustering
    • Hartigan, J. A., Statistical theory in clustering, J. Classification 2, 63-76 (1975).
    • (1975) J. Classification , vol.2 , pp. 63-76
    • Hartigan, J.A.1
  • 26
    • 0034568109 scopus 로고    scopus 로고
    • "Gene shaving" as a method for identifying distinct sets of genes with similar expression patterns
    • research
    • Hastie, T., Tibshirani, R., Eisen, M. B., Alizadeh, A., Levy, R., Staudt, L., Chan, W. C., Botstein, D., and Brown, P., "Gene shaving" as a method for identifying distinct sets of genes with similar expression patterns, Genome Biol. 1, research0003.1-0003.21 (2000).
    • (2000) Genome Biol. , vol.1 , pp. 0003.1-0003.21
    • Hastie, T.1    Tibshirani, R.2    Eisen, M.B.3    Alizadeh, A.4    Levy, R.5    Staudt, L.6    Chan, W.C.7    Botstein, D.8    Brown, P.9
  • 29
    • 0034921979 scopus 로고    scopus 로고
    • Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data
    • Ideker, T., Thorsson, V., Siegel, A. F., and Hood, L. E., Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data, J. Comput. Biol. 7, 805-817 (2000).
    • (2000) J. Comput. Biol. , vol.7 , pp. 805-817
    • Ideker, T.1    Thorsson, V.2    Siegel, A.F.3    Hood, L.E.4
  • 31
    • 33746257145 scopus 로고    scopus 로고
    • The practice of cluster analysis
    • Kettenring, J. R., The practice of cluster analysis, J Classification 23, 3-30 (2006).
    • (2006) J Classification , vol.23 , pp. 3-30
    • Kettenring, J.R.1
  • 32
    • 0034730124 scopus 로고    scopus 로고
    • Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations
    • USA
    • Lee, M. L. T., Kuo, F. C., Whitmore, G. A., and Sklar, J., Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations, Proc. Natl. Acad. Sci. USA 97, 9834-9838 (2000).
    • (2000) Proc. Natl. Acad. Sci. , vol.97 , pp. 9834-9838
    • Lee, M.L.T.1    Kuo, F.C.2    Whitmore, G.A.3    Sklar, J.4
  • 33
    • 15044339834 scopus 로고    scopus 로고
    • Bayesian clustering with variable and transformation selections
    • Bernardo, J. M., Bayarri, M. J., Berger, J. O., Dawid, A. P., Heckerman, D., Smith, A. F. M., and West, M., eds., Oxford Univ. Press, Oxford, UK
    • Liu, J. S., Zhang, J. L., Palumbo, M. J., and Lawrence, C. E., Bayesian clustering with variable and transformation selections, in Bayesian Statistics, Bernardo, J. M., Bayarri, M. J., Berger, J. O., Dawid, A. P., Heckerman, D., Smith, A. F. M., and West, M., eds., Oxford Univ. Press, Oxford, UK, 2003, vol. 7, pp. 249-275.
    • (2003) Bayesian Statistics , vol.7 , pp. 249-275
    • Liu, J.S.1    Zhang, J.L.2    Palumbo, M.J.3    Lawrence, C.E.4
  • 34
    • 0037339264 scopus 로고    scopus 로고
    • Clustering of time-course gene expression data using a mixed-effects model with B-splines
    • Luan, Y. and Li, H., Clustering of time-course gene expression data using a mixed-effects model with B-splines, Bioinformatics 19, 474-482 (2003).
    • (2003) Bioinformatics , vol.19 , pp. 474-482
    • Luan, Y.1    Li, H.2
  • 35
    • 0004138922 scopus 로고
    • The Interpretation of Multiple Observations
    • Academic Press, London
    • Marriott, F. H. C., The Interpretation of Multiple Observations, Academic Press, London, 1974.
    • (1974)
    • Marriott, F.H.C.1
  • 36
    • 0003646026 scopus 로고    scopus 로고
    • Generalized, Linear, and Mixed Models
    • Wiley, New York
    • McCulloch, C. E. and Searle, S. R., Generalized, Linear, and Mixed Models, Wiley, New York, 2001.
    • (2001)
    • McCulloch, C.E.1    Searle, S.R.2
  • 37
    • 0023570352 scopus 로고
    • On bootstrapping the likelihood ratio test statistic for the number of components in a normal mixture
    • McLachlan, G. J., On bootstrapping the likelihood ratio test statistic for the number of components in a normal mixture, Appl. Statist. 36, 318-324 (1987).
    • (1987) Appl. Statist. , vol.36 , pp. 318-324
    • McLachlan, G.J.1
  • 38
    • 0003891734 scopus 로고
    • Mixture Models: Inference and Applications to Clustering
    • Marcel Dekker, New York
    • McLachlan, G. J. and Basford, K. E., Mixture Models: Inference and Applications to Clustering, Marcel Dekker, New York, (1988).
    • (1988)
    • McLachlan, G.J.1    Basford, K.E.2
  • 39
    • 0036203115 scopus 로고    scopus 로고
    • A mixture model-based approach to the clustering of microarray expression data
    • McLachlan, G. J., Bean, R. W., and Peel, D., A mixture model-based approach to the clustering of microarray expression data, Bioinformatics 18, 413-422 (2002).
    • (2002) Bioinformatics , vol.18 , pp. 413-422
    • McLachlan, G.J.1    Bean, R.W.2    Peel, D.3
  • 40
    • 15044352042 scopus 로고    scopus 로고
    • Analyzing Microarray Gene Expression Data
    • Wiley, Hoboken, NJ
    • McLachlan, G. J., Do, K. A., and Ambroise, C., Analyzing Microarray Gene Expression Data, Wiley, Hoboken, NJ, (2004).
    • (2004)
    • McLachlan, G.J.1    Do, K.A.2    Ambroise, C.3
  • 41
    • 23744437299 scopus 로고    scopus 로고
    • On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples
    • McLachlan, G. J. and Khan, N., On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples, J. Multivar. Anal. 90, 90-105 (2004).
    • (2004) J. Multivar. Anal. , vol.90 , pp. 90-105
    • McLachlan, G.J.1    Khan, N.2
  • 42
    • 0004066260 scopus 로고    scopus 로고
    • Finite Mixture Models
    • Wiley, New York
    • McLachlan, G. J. and Peel, D., Finite Mixture Models, Wiley, New York, 2000.
    • (2000)
    • McLachlan, G.J.1    Peel, D.2
  • 43
    • 0036739286 scopus 로고    scopus 로고
    • Bayesian infinite mixture model based clustering of gene expression profiles
    • Medvedovic, M. and Sivaganesan, S., Bayesian infinite mixture model based clustering of gene expression profiles, Bioinformatics 18, 1194-1206 (2002).
    • (2002) Bioinformatics , vol.18 , pp. 1194-1206
    • Medvedovic, M.1    Sivaganesan, S.2
  • 45
    • 33645225998 scopus 로고    scopus 로고
    • The EM algorithm
    • Gentle, J., Hardle, W., and Mori, Y., eds, Springer-Verlag, New York
    • Ng, S. K., Krishnan, T., and McLachlan, G. J., The EM algorithm, in Handbook of Computational Statistics, Gentle, J., Hardle, W., and Mori, Y., eds, Springer-Verlag, New York, Vol. 1, pp. 137-168 (2004).
    • (2004) Handbook of Computational Statistics , vol.1 , pp. 137-168
    • Ng, S.K.1    Krishnan, T.2    McLachlan, G.J.3
  • 46
    • 84954579537 scopus 로고    scopus 로고
    • A mixture model with random-effects components for clustering correlated gene-expression profiles
    • (in press)
    • Ng, S. K., McLachlan, G. J., Wang, K., Ben-Tovim, L., and Ng, S. W., A mixture model with random-effects components for clustering correlated gene-expression profiles, (in press).
    • Ng, S.K.1    McLachlan, G.J.2    Wang, K.3    Ben-Tovim, L.4    Ng, S.W.5
  • 47
    • 33645228523 scopus 로고    scopus 로고
    • Multilevel modelling for inference of genetic regulatory networks
    • Bender, A., ed., International Society for Optical Engineering, Bellingham, WA
    • Ng, S. K., Wang, K., and McLachlan, G. J., Multilevel modelling for inference of genetic regulatory networks, in Proc. SPIE 2005, Complex Systems in the Int. Symp. Microelectronics, MEMS, and Nanotechnology, Bender, A., ed., International Society for Optical Engineering, Bellingham, WA, 2006, Vol. 6039, pp. 60390S-1-60390S-12.
    • (2006) Proc. SPIE 2005, Complex Systems in the Int. Symp. Microelectronics, MEMS, and Nanotechnology , vol.6039 , pp. 60390S-1
    • Ng, S.K.1    Wang, K.2    McLachlan, G.J.3
  • 48
    • 33645289673 scopus 로고    scopus 로고
    • Incorporating gene functions as priors in model-based clustering of microarray gene expression data
    • Pan, W. Incorporating gene functions as priors in model-based clustering of microarray gene expression data, Bioinformatics 22(7) 795-801 (2006).
    • (2006) Bioinformatics , vol.22 , Issue.7 , pp. 795-801
    • Pan, W.1
  • 49
    • 0036372266 scopus 로고    scopus 로고
    • Model-based cluster analysis of microarray gene-expression data
    • research
    • Pan, W., Lin, J., and Le, C. T., Model-based cluster analysis of microarray gene-expression data, Genome Biol. 3, research0009.1-0009.8 (2002).
    • (2002) Genome Biol. , vol.3 , pp. 0009.1-0009.8
    • Pan, W.1    Lin, J.2    Le, C.T.3
  • 50
    • 0141871186 scopus 로고    scopus 로고
    • The Analysis of Gene Expression Data
    • Springer-Verlag, New York
    • Parmigiani, G., Garrett, E. S., Irizarry, R. A., and Zeger, S. L., eds., The Analysis of Gene Expression Data, Springer-Verlag, New York, 2003.
    • (2003)
    • Parmigiani, G.1    Garrett, E.S.2    Irizarry, R.A.3    Zeger, S.L.4
  • 51
    • 0141626917 scopus 로고    scopus 로고
    • The effect of replication on gene expression microarray experiments
    • Pavlidis, P., Li, Q., and Noble, W. S., The effect of replication on gene expression microarray experiments, Bioinformatics, 19, 1620-1627 (2003).
    • (2003) Bioinformatics , vol.19 , pp. 1620-1627
    • Pavlidis, P.1    Li, Q.2    Noble, W.S.3
  • 52
    • 0036129820 scopus 로고    scopus 로고
    • Statistical inference for simultaneous clustering of gene expression data
    • Pollard, K. S. and van der Laan, M. J., Statistical inference for simultaneous clustering of gene expression data, Math. Biosci. 176, 99-121 (2002).
    • (2002) Math. Biosci. , vol.176 , pp. 99-121
    • Pollard, K.S.1    van der Laan, M.J.2
  • 53
    • 17244378918 scopus 로고    scopus 로고
    • A rapid method for the comparison of cluster analyses, Statistica Sinica
    • Reilly, C., Wang, C., and Rutherford, R., A rapid method for the comparison of cluster analyses, Statistica Sinica 15, 19-33 (2005).
    • (2005) , vol.15 , pp. 19-33
    • Reilly, C.1    Wang, C.2    Rutherford, R.3
  • 54
    • 0037606155 scopus 로고    scopus 로고
    • Approximate variance-stabilizing transformations for a gene-expression microarray data
    • Rocke, D. M. and Durbin, B., Approximate variance-stabilizing transformations for a gene-expression microarray data, Bioinformatics 19, 966-972 (2003).
    • (2003) Bioinformatics , vol.19 , pp. 966-972
    • Rocke, D.M.1    Durbin, B.2
  • 55
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwarz, G., Estimating the dimension of a model, Ann. Statist. 6, 461-464 (1978).
    • (1978) Ann. Statist. , vol.6 , pp. 461-464
    • Schwarz, G.1
  • 56
    • 15944365840 scopus 로고    scopus 로고
    • Diagnostic signatures from microarrays: A bioinformatics concept for personalized medicine
    • Spang, R., Diagnostic signatures from microarrays: A bioinformatics concept for personalized medicine, Biosilico 1, 64-68 (2003).
    • (2003) Biosilico , vol.1 , pp. 64-68
    • Spang, R.1
  • 57
    • 1242323130 scopus 로고    scopus 로고
    • Statistical Analysis of Gene Expression Microarray Data
    • Chapman & Hall/CRC, Boca Raton, FL
    • Speed, T., ed., Statistical Analysis of Gene Expression Microarray Data. Chapman & Hall/CRC, Boca Raton, FL, 2003.
    • (2003)
    • Speed, T.1
  • 58
    • 0031742022 scopus 로고    scopus 로고
    • Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization
    • Spellman, P., Sherlock, G., Zhang, M. Q., Iyer, V. R., Anders, K., Eisen, M. B., Brown, P. O., Botstein, D., and Futcher, B., Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization, Molec. Biol. Cell 9, 3273-3297 (1998).
    • (1998) Molec. Biol. Cell , vol.9 , pp. 3273-3297
    • Spellman, P.1    Sherlock, G.2    Zhang, M.Q.3    Iyer, V.R.4    Anders, K.5    Eisen, M.B.6    Brown, P.O.7    Botstein, D.8    Futcher, B.9
  • 60
    • 0034782618 scopus 로고    scopus 로고
    • Model-based clustering and data transformations for gene expression data
    • Yeung, K. Y., Fraley, C., Murua, A., Raftery, A. E., and Ruzzo, W. L. Model-based clustering and data transformations for gene expression data, Bioinformatics 17, 977-987 (2001).
    • (2001) Bioinformatics , vol.17 , pp. 977-987
    • Yeung, K.Y.1    Fraley, C.2    Murua, A.3    Raftery, A.E.4    Ruzzo, W.L.5
  • 61
    • 0001665174 scopus 로고
    • Statistical modeling of data on teaching styles
    • Aitkin, M., Anderson, D., and Hinde, J., Statistical modeling of data on teaching styles, J. Roy. Statist. Soc. 144(4), 419-461 (1981).
    • (1981) J. Roy. Statist. Soc. , vol.144 , Issue.4 , pp. 419-461
    • Aitkin, M.1    Anderson, D.2    Hinde, J.3
  • 62
    • 23844434593 scopus 로고    scopus 로고
    • Unsupervised pattern recognition: An introduction to the whys and wherefores of clustering microarray data
    • Boutros, P. C. and Okey, A. B., Unsupervised pattern recognition: An introduction to the whys and wherefores of clustering microarray data, Br. Bioinf. 6(4), 331-343 (2005).
    • (2005) Br. Bioinf. , vol.6 , Issue.4 , pp. 331-343
    • Boutros, P.C.1    Okey, A.B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.