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Volumn 6, Issue 1, 2011, Pages

A robust approach based on Weibull distribution for clustering gene expression data

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EID: 79957580563     PISSN: None     EISSN: 17487188     Source Type: Journal    
DOI: 10.1186/1748-7188-6-14     Document Type: Article
Times cited : (17)

References (29)
  • 4
    • 27944458009 scopus 로고    scopus 로고
    • Chips to Hits: microarray and microfluidic technologies for high-throughput analysis and drug discovery. September 12-15, 2005, MA, USA
    • 10.1586/14737159.5.6.843, 16255625
    • Khademhosseini A. Chips to Hits: microarray and microfluidic technologies for high-throughput analysis and drug discovery. September 12-15, 2005, MA, USA. Expert Rev Mol Diagn 2005, 5:843-846. 10.1586/14737159.5.6.843, 16255625.
    • (2005) Expert Rev Mol Diagn , vol.5 , pp. 843-846
    • Khademhosseini, A.1
  • 6
    • 0032402904 scopus 로고    scopus 로고
    • Technology for microarray analysis of gene expression
    • 10.1016/S0958-1669(98)80138-9, 9889134
    • Watson A, Mazumder A, Stewart M, Balasubramanian S. Technology for microarray analysis of gene expression. Curr Opin Biotechnol 1998, 9:609-614. 10.1016/S0958-1669(98)80138-9, 9889134.
    • (1998) Curr Opin Biotechnol , vol.9 , pp. 609-614
    • Watson, A.1    Mazumder, A.2    Stewart, M.3    Balasubramanian, S.4
  • 7
    • 0032728081 scopus 로고    scopus 로고
    • Clustering gene expression patterns
    • 10.1089/106652799318274, 10582567
    • Ben-Dor A, Shamir R, Yakhini Z. Clustering gene expression patterns. J Comput Biol 1999, 6:281-297. 10.1089/106652799318274, 10582567.
    • (1999) J Comput Biol , vol.6 , pp. 281-297
    • Ben-Dor, A.1    Shamir, R.2    Yakhini, Z.3
  • 8
    • 0036115902 scopus 로고    scopus 로고
    • Introduction to hierarchical clustering
    • 10.1097/00004691-200203000-00005, 11997725
    • Guess MJ, Wilson SB. Introduction to hierarchical clustering. J Clin Neurophysiol 2002, 19:144-151. 10.1097/00004691-200203000-00005, 11997725.
    • (2002) J Clin Neurophysiol , vol.19 , pp. 144-151
    • Guess, M.J.1    Wilson, S.B.2
  • 9
    • 22944463621 scopus 로고    scopus 로고
    • Clustering algorithms and other exploratory methods for microarray data analysis
    • Rahnenfuhrer J. Clustering algorithms and other exploratory methods for microarray data analysis. Methods Inf Med 2005, 44:444-448.
    • (2005) Methods Inf Med , vol.44 , pp. 444-448
    • Rahnenfuhrer, J.1
  • 10
    • 23844434593 scopus 로고    scopus 로고
    • Unsupervised pattern recognition: an introduction to the whys and wherefores of clustering microarray data
    • 10.1093/bib/6.4.331, 16420732
    • Boutros PC, Okey AB. Unsupervised pattern recognition: an introduction to the whys and wherefores of clustering microarray data. Brief Bioinform 2005, 6:331-343. 10.1093/bib/6.4.331, 16420732.
    • (2005) Brief Bioinform , vol.6 , pp. 331-343
    • Boutros, P.C.1    Okey, A.B.2
  • 11
    • 0034322441 scopus 로고    scopus 로고
    • Reclassification as supervised clustering
    • 10.1162/089976600300014836, 11110126
    • Sierra A, Corbacho F. Reclassification as supervised clustering. Neural Comput 2000, 12:2537-2546. 10.1162/089976600300014836, 11110126.
    • (2000) Neural Comput , vol.12 , pp. 2537-2546
    • Sierra, A.1    Corbacho, F.2
  • 12
    • 0001457509 scopus 로고
    • Some Methods for classification and Analysis of Multivariate Observations
    • University of California Press
    • MacQueen JB. Some Methods for classification and Analysis of Multivariate Observations. the 5th Berkeley Symposium on Mathematical Statistics and Probability 1967, 281-297. University of California Press.
    • (1967) the 5th Berkeley Symposium on Mathematical Statistics and Probability , pp. 281-297
    • MacQueen, J.B.1
  • 13
    • 0041807960 scopus 로고    scopus 로고
    • K-means clustering method for auditory evoked potentials selection
    • 10.1007/BF02348081, 12892361
    • Gourevitch B, Le Bouquin-Jeannes R. K-means clustering method for auditory evoked potentials selection. Med Biol Eng Comput 2003, 41:397-402. 10.1007/BF02348081, 12892361.
    • (2003) Med Biol Eng Comput , vol.41 , pp. 397-402
    • Gourevitch, B.1    Le Bouquin-Jeannes, R.2
  • 14
    • 9144249823 scopus 로고    scopus 로고
    • SOM-based algorithms for qualitative variables
    • 10.1016/j.neunet.2004.07.010, 15555858
    • Cottrell M, Ibbou S, Letremy P. SOM-based algorithms for qualitative variables. Neural Netw 2004, 17:1149-1167. 10.1016/j.neunet.2004.07.010, 15555858.
    • (2004) Neural Netw , vol.17 , pp. 1149-1167
    • Cottrell, M.1    Ibbou, S.2    Letremy, P.3
  • 15
    • 33749179701 scopus 로고    scopus 로고
    • Application of the self-organizing map (SOM) to assess the heavy metal removal performance in experimental constructed wetlands
    • 10.1016/j.watres.2006.07.027, 16982080
    • Lee BH, Scholz M. Application of the self-organizing map (SOM) to assess the heavy metal removal performance in experimental constructed wetlands. Water Res 2006, 40:3367-3374. 10.1016/j.watres.2006.07.027, 16982080.
    • (2006) Water Res , vol.40 , pp. 3367-3374
    • Lee, B.H.1    Scholz, M.2
  • 16
    • 84987266075 scopus 로고
    • A statistical distribution function of wide applicability
    • Weibull W. A statistical distribution function of wide applicability. J Appl Mech-Trans ASME 1951, 18:293-297.
    • (1951) J Appl Mech-Trans ASME , vol.18 , pp. 293-297
    • Weibull, W.1
  • 17
    • 0001087235 scopus 로고
    • The empirical distribution function with arbitrarily grouped, censored and truncated data
    • Turnbull BW. The empirical distribution function with arbitrarily grouped, censored and truncated data. Journal of the Royal Statistical Society Series B 1976, 38:290-295.
    • (1976) Journal of the Royal Statistical Society Series B , vol.38 , pp. 290-295
    • Turnbull, B.W.1
  • 19
    • 35348999644 scopus 로고    scopus 로고
    • Modification of Kolmogorov-Smirnov test for DNA content data analysis through distribution alignment
    • 10.1089/adt.2007.071, 17939753
    • Huang S, Yeo AA, Li SD. Modification of Kolmogorov-Smirnov test for DNA content data analysis through distribution alignment. Assay Drug Dev Technol 2007, 5:663-671. 10.1089/adt.2007.071, 17939753.
    • (2007) Assay Drug Dev Technol , vol.5 , pp. 663-671
    • Huang, S.1    Yeo, A.A.2    Li, S.D.3
  • 20
    • 0014272312 scopus 로고
    • The Kolmogorov-Smirnov test for the log-normality of sample cumulative frequency distributions
    • Ong LD, LeClare PC. The Kolmogorov-Smirnov test for the log-normality of sample cumulative frequency distributions. Health Phys 1968, 14:376.
    • (1968) Health Phys , vol.14 , pp. 376
    • Ong, L.D.1    LeClare, P.C.2
  • 21
    • 35348889464 scopus 로고
    • Finding Clusters: An application of the Distance Concept
    • Clason R. Finding Clusters: An application of the Distance Concept. The Mathematics Teacher 1990,
    • (1990) The Mathematics Teacher
    • Clason, R.1
  • 22
    • 54049099562 scopus 로고    scopus 로고
    • The Gene Ontology (GO) project: structured vocabularies for molecular biology and their application to genome and expression analysis
    • Unit 7 2
    • Blake JA, Harris MA. The Gene Ontology (GO) project: structured vocabularies for molecular biology and their application to genome and expression analysis. Curr Protoc Bioinformatics 2008, 7. Unit 7 2.
    • (2008) Curr Protoc Bioinformatics , vol.7
    • Blake, J.A.1    Harris, M.A.2
  • 23
    • 61449172037 scopus 로고    scopus 로고
    • Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
    • Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009, 4:44-57.
    • (2009) Nat Protoc , vol.4 , pp. 44-57
    • Huang da, W.1    Sherman, B.T.2    Lempicki, R.A.3
  • 24
    • 0035024021 scopus 로고    scopus 로고
    • Validating clustering for gene expression data
    • 10.1093/bioinformatics/17.4.309, 11301299
    • Yeung KY, Haynor DR, Ruzzo WL. Validating clustering for gene expression data. Bioinformatics 2001, 17:309-318. 10.1093/bioinformatics/17.4.309, 11301299.
    • (2001) Bioinformatics , vol.17 , pp. 309-318
    • Yeung, K.Y.1    Haynor, D.R.2    Ruzzo, W.L.3
  • 26
    • 70449504238 scopus 로고    scopus 로고
    • Identification of functionally related genes using data mining and data integration: a breast cancer case study
    • 10.1186/1471-2105-10-S12-S8, 2788359, 19958518
    • Mosca E, Bertoli G, Piscitelli E, Vilardo L, Reinbold RA, Zucchi I, Milanesi L. Identification of functionally related genes using data mining and data integration: a breast cancer case study. BMC Bioinformatics 2009, 10(Suppl 12):S8. 10.1186/1471-2105-10-S12-S8, 2788359, 19958518.
    • (2009) BMC Bioinformatics , vol.10 , Issue.SUPPL. 12
    • Mosca, E.1    Bertoli, G.2    Piscitelli, E.3    Vilardo, L.4    Reinbold, R.A.5    Zucchi, I.6    Milanesi, L.7


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