메뉴 건너뛰기




Volumn 21, Issue 6, 2014, Pages 428-445

Biological cluster evaluation for gene function prediction

Author keywords

algorithms; biochemical networks; combinatorics; computational molecular biology; databases; functional genomics; gene expression; NP completeness

Indexed keywords

ARABIDOPSIS; FUNGAL GENE; GENE EXPRESSION REGULATION; GENETICS; INFORMATION PROCESSING; PHYSIOLOGY; PLANT GENE; SACCHAROMYCES CEREVISIAE;

EID: 84901975336     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.2009.0129     Document Type: Article
Times cited : (9)

References (59)
  • 1
    • 0034069495 scopus 로고    scopus 로고
    • Gene ontology: Tool for the unification of biology
    • Ashburner, M. 2000. Gene ontology: Tool for the unification of biology. Nat. Genet. 25, 25-29
    • (2000) Nat. Genet , vol.25 , pp. 25-29
    • Ashburner, M.1
  • 2
  • 3
    • 0033280561 scopus 로고    scopus 로고
    • A survey of fuzzy clustering algorithms for pattern recognition
    • Baraldi, A., and Blonda, P. 1999. A survey of fuzzy clustering algorithms for pattern recognition. IEEE Trans. Syst. Man Cybernet. B Cybernet. 29, 778-785
    • (1999) IEEE Trans. Syst. Man Cybernet. B Cybernet , vol.29 , pp. 778-785
    • Baraldi, A.1    Blonda, P.2
  • 5
    • 33745796330 scopus 로고    scopus 로고
    • Incorporating biological domain knowledge into cluster validity assessment
    • Bolshakova, N., Azuaje, F., and Cunningham, P. 2006. Incorporating biological domain knowledge into cluster validity assessment. Lect. Notes Comput. Sci. 3907, 13-22
    • (2006) Lect. Notes Comput. Sci , vol.3907 , pp. 13-22
    • Bolshakova, N.1    Azuaje, F.2    Cunningham, P.3
  • 9
    • 33749428430 scopus 로고    scopus 로고
    • Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes
    • Datta, S., and Datta, S. 2006. Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes. BMC Bioinform. 7, 1-9
    • (2006) BMC Bioinform , vol.7 , pp. 1-9
    • Datta, S.1    Datta, S.2
  • 11
    • 28644449917 scopus 로고    scopus 로고
    • How does gene expression clustering work?
    • D'haeseleer, P. 2005. How does gene expression clustering work?. Nat. Biotechnol. 23, 1499-1501
    • (2005) Nat. Biotechnol , vol.23 , pp. 1499-1501
    • D'haeseleer, P.1
  • 12
    • 84941155240 scopus 로고
    • Well-separated clusters and fuzzy partitions
    • Dunn, J.C. 1974. Well-separated clusters and fuzzy partitions. J. Cybernet. 4, 95-104
    • (1974) J. Cybernet , vol.4 , pp. 95-104
    • Dunn, J.C.1
  • 13
    • 33847629328 scopus 로고    scopus 로고
    • The effect of weight on community structure of networks
    • Fan, Y., Li, M., P. Zhang, et al. 2006. The effect of weight on community structure of networks. Physica A Statist. Mech. Appl. 378, 583-590
    • (2006) Physica A Statist. Mech. Appl , vol.378 , pp. 583-590
    • Fan, Y.1    Li, M.2    Zhang, P.3
  • 14
    • 22544432531 scopus 로고    scopus 로고
    • Noise-robust soft clustering of gene expression time-course data
    • Futschik, M.E., and Carlisle, B. 2005. Noise-robust soft clustering of gene expression time-course data. J. Bioinform. Comput. Biol. 3, 965-988
    • (2005) J. Bioinform. Comput. Biol , vol.3 , pp. 965-988
    • Futschik, M.E.1    Carlisle, B.2
  • 15
    • 62849090487 scopus 로고    scopus 로고
    • Computational cluster validation for microarray data analysis: Experimental assessment of clest, consensus clustering, figure of merit, gap statistics and model explorer
    • Giancarlo, R., Scaturro, D., and Utro, F. 2008. Computational cluster validation for microarray data analysis: Experimental assessment of clest, consensus clustering, figure of merit, gap statistics and model explorer. BMC Bioinform. 9, 462
    • (2008) BMC Bioinform , vol.9 , pp. 462
    • Giancarlo, R.1    Scaturro, D.2    Utro, F.3
  • 16
    • 0036798238 scopus 로고    scopus 로고
    • Judging the quality of gene expression-based clustering methods using gene annotation
    • DOI 10.1101/gr.397002
    • 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. (Pubitemid 35175096)
    • (2002) Genome Research , vol.12 , Issue.10 , pp. 1574-1581
    • Gibbons, F.D.1    Roth, F.P.2
  • 17
    • 33645821454 scopus 로고    scopus 로고
    • Assessing semantic similarity measures for the characterization of human regulatory pathways
    • Guo, X., Liu, R., Shriver, C.D., et al. 2006. Assessing semantic similarity measures for the characterization of human regulatory pathways. Bioinformatics 22, 967-973
    • (2006) Bioinformatics , vol.22 , pp. 967-973
    • Guo, X.1    Liu, R.2    Shriver, C.D.3
  • 20
    • 25144456056 scopus 로고    scopus 로고
    • Computational cluster validation in post-genomic data analysis
    • DOI 10.1093/bioinformatics/bti517
    • Handl, J., Knowles, J., and Kell, D.B. 2005. Computational cluster validation in post-genomic data analysis. Bioinformatics 21, 3201-3212. (Pubitemid 41418432)
    • (2005) Bioinformatics , vol.21 , Issue.15 , pp. 3201-3212
    • Handl, J.1    Knowles, J.2    Kell, D.B.3
  • 24
    • 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
  • 25
  • 26
    • 33749138913 scopus 로고    scopus 로고
    • Generating random correlation matrices based on partial correlations
    • Joe, H. 2006. Generating random correlation matrices based on partial correlations. J. Multivar. Anal. 97, 2177-2189
    • (2006) J. Multivar. Anal , vol.97 , pp. 2177-2189
    • Joe, H.1
  • 27
    • 0033335479 scopus 로고    scopus 로고
    • Approximation algorithms for classification problems with pairwise relationships: Metric labelling and Markov random fields
    • Kleinberg, J.M., and Tardos, E. 2002. Approximation algorithms for classification problems with pairwise relationships: Metric labelling and Markov random fields. J. ACM 49, 14-23
    • (2002) J. ACM , vol.49 , pp. 14-23
    • Kleinberg, J.M.1    Tardos, E.2
  • 29
    • 0005180705 scopus 로고    scopus 로고
    • An information-Theoretic definition of similarity
    • Lin, D. 1998. An information-Theoretic definition of similarity. Proc. 15th Int. Conf. Mach. Learn. 296-304
    • (1998) Proc. 15th Int. Conf. Mach. Learn , pp. 296-304
    • Lin, D.1
  • 30
    • 0037480738 scopus 로고    scopus 로고
    • Investigating semantic similarity measures across the gene ontology: The relationship between sequence and annotation
    • DOI 10.1093/bioinformatics/btg153
    • Lord, P.W., Stevens, R.D., Brass, A., et al. 2003. Investigating semantic similarity measures across the gene ontology: The relationship between sequence and annotation. Bioinformatics 19, 1275-1283. (Pubitemid 36850221)
    • (2003) Bioinformatics , vol.19 , Issue.10 , pp. 1275-1283
    • Lord, P.W.1    Stevens, R.D.2    Brass, A.3    Goble, C.A.4
  • 32
    • 0000272920 scopus 로고
    • An algorithm for generating artificial test clusters
    • Milligan, G.W. 1985. An algorithm for generating artificial test clusters. Psychometrika 50, 123-127
    • (1985) Psychometrika , vol.50 , pp. 123-127
    • Milligan, G.W.1
  • 33
    • 0042572077 scopus 로고    scopus 로고
    • Receptor-like protein kinases: The keys to response
    • Morris, E.R., and Walker, J.C. 2003. Receptor-like protein kinases: The keys to response. Curr. Opin. Plant Biol. 6, 339-342
    • (2003) Curr. Opin. Plant Biol , vol.6 , pp. 339-342
    • Morris, E.R.1    Walker, J.C.2
  • 34
    • 0034646512 scopus 로고    scopus 로고
    • PHAX, a mediator of U snRNA nuclear export whose activity is regulated by phosphorylation
    • DOI 10.1016/S0092-8674(00)80829-6
    • Ohno, M., Segref, A., Bachi, A., et al. 2000. Phax, a mediator of u snRNA nuclear export whose activity is regulated by phosphorylation. Cell 101, 187-198. (Pubitemid 32004746)
    • (2000) Cell , vol.101 , Issue.2 , pp. 187-198
    • Ohno, M.1    Segref, A.2    Bachi, A.3    Wilm, M.4    Mattaj, I.W.5
  • 35
    • 0018306059 scopus 로고
    • A threshold selection method from greylevel histograms
    • Otsu, N. 1979. A threshold selection method from greylevel histograms. IEEE Trans. Syst. Man Cybernet. 9, 62-66
    • (1979) IEEE Trans Syst. Man Cybernet , vol.9 , pp. 62-66
    • Otsu, N.1
  • 36
    • 20444504323 scopus 로고    scopus 로고
    • Uncovering the overlapping community structure of complex networks in nature and society
    • DOI 10.1038/nature03607
    • Palla, G., Derenyi, I., Farkas, I., et al. 2005. Uncovering the overlapping community structure of complex networks in nature and society. Nature 435, 814-818. (Pubitemid 40839731)
    • (2005) Nature , vol.435 , Issue.7043 , pp. 814-818
    • Palla, G.1    Derenyi, I.2    Farkas, I.3    Vicsek, T.4
  • 37
    • 49549101132 scopus 로고    scopus 로고
    • Functional coherence in domain interaction networks
    • Pandey, J., Koyutrk, M., Subramaniam, S., et al. 2008. Functional coherence in domain interaction networks. Bioinformatics 24, i28-i34
    • (2008) Bioinformatics , vol.24
    • Pandey, J.1    Koyutrk, M.2    Subramaniam, S.3
  • 38
    • 2942729600 scopus 로고    scopus 로고
    • New indices for analysing partial ranking diagrams
    • Pavan, M., and Todeschini, R. 2004. New indices for analysing partial ranking diagrams. Anal. Chem. Acta 515, 167-181
    • (2004) Anal. Chem. Acta , vol.515 , pp. 167-181
    • Pavan, M.1    Todeschini, R.2
  • 39
    • 34548573170 scopus 로고    scopus 로고
    • Why are there still over 1000 uncharacterized yeast genes?
    • Pena-Castillo, L., and Hughes, T.R 2007. Why are there still over 1000 uncharacterized yeast genes?. Genetics 176, 7-14
    • (2007) Genetics , vol.176 , pp. 7-14
    • Pena-Castillo, L.1    Hughes, T.R.2
  • 40
    • 57249103315 scopus 로고    scopus 로고
    • Deriving distance metrics from generality relations
    • Raedt, L.D., and Ramon, J. 2009. Deriving distance metrics from generality relations. Patt. Recogn. Lett. 30, 187-191
    • (2009) Patt. Recogn. Lett , vol.30 , pp. 187-191
    • Raedt, L.D.1    Ramon, J.2
  • 41
    • 25444468618 scopus 로고    scopus 로고
    • Molecular biology-Noise in gene expression: Origins, consequences, and control
    • DOI 10.1126/science.1105891
    • Raser, J.M., and O'Shea, E.K. 2005. Noise in gene expression: Origins, consequences, and control. Science 309, 2010-2013. (Pubitemid 41362308)
    • (2005) Science , vol.309 , Issue.5743 , pp. 2010-2013
    • Raser, J.M.1    O'Shea, E.K.2
  • 42
    • 2342501846 scopus 로고    scopus 로고
    • Development and evaluation of an Arabidopsis whole genome Affymetrix probe array
    • DOI 10.1111/j.1365-313X.2004.02061.x
    • Redman, J.C., Haas, B.J., Tanimoto, G., et al. 2004. Development and evaluation of an arabidopsis whole genome affymetrix probe array. Plant J. 38, 545-561. (Pubitemid 38601050)
    • (2004) Plant Journal , vol.38 , Issue.3 , pp. 545-561
    • Redman, J.C.1    Haas, B.J.2    Tanimoto, G.3    Town, C.D.4
  • 43
    • 0003033112 scopus 로고
    • Using information content to evaluate semantic similarity in a taxonomy
    • Resnik, P. 1995. Using information content to evaluate semantic similarity in a taxonomy. Proc. 14th Int. Joint Conf. Artif. Intell. 448-453
    • (1995) Proc. 14th Int. Joint Conf. Artif. Intell , pp. 448-453
    • Resnik, P.1
  • 44
    • 0023453329 scopus 로고
    • Silhouettes: A graphical aid to the interpretation and validation of cluster analysis
    • Rousseeuw, P.J. 1987. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53-65
    • (1987) J. Comput. Appl. Math , vol.20 , pp. 53-65
    • Rousseeuw, P.J.1
  • 45
    • 37849020436 scopus 로고    scopus 로고
    • Decoding genes with coexpression networks and metabolomics majority report by precogs
    • Saito, K., Hirai, M.Y., and Yonekura-Sakakibara, K. 2008. Decoding genes with coexpression networks and metabolomics majority report by precogs. Trends Plant Sci. 13, 36-43
    • (2008) Trends Plant Sci , vol.13 , pp. 36-43
    • Saito, K.1    Hirai, M.Y.2    Yonekura-Sakakibara, K.3
  • 46
    • 35248893285 scopus 로고    scopus 로고
    • Graph clustering
    • Schaeffer, E. 2007. Graph clustering. Comput. Sci. Rev. 1, 27-64
    • (2007) Comput. Sci. Rev , vol.1 , pp. 27-64
    • Schaeffer, E.1
  • 47
    • 34248576303 scopus 로고    scopus 로고
    • Functional evaluation of domain-domain interactions and human protein interaction networks
    • DOI 10.1093/bioinformatics/btm012
    • Schlicker, A., Huthmacher, C., Ramirez, F., et al. 2007. Functional evaluation of domain-domain interactions and human protein interaction networks. Bioinformatics 23, 859-865. (Pubitemid 47049920)
    • (2007) Bioinformatics , vol.23 , Issue.7 , pp. 859-865
    • Schlicker, A.1    Huthmacher, C.2    Ramirez, F.3    Lengauer, T.4    Albrecht, M.5
  • 49
    • 33749431392 scopus 로고    scopus 로고
    • Validation and functional annotation of expression-based clusters based on gene ontology
    • Steuer, R., Humburg, P., and Selbig, J. 2006. Validation and functional annotation of expression-based clusters based on gene ontology. BMC Bioinform. 7, 380
    • (2006) BMC Bioinform , vol.7 , pp. 380
    • Steuer, R.1    Humburg, P.2    Selbig, J.3
  • 50
    • 0033028596 scopus 로고    scopus 로고
    • Systematic determination of genetic network architecture
    • Tavazoie, S., Hughes, J., Campbell, M., et al. 1999. Systematic determination of genetic network architecture. Nat. Genet. 22, 218-285
    • (1999) Nat. Genet , vol.22 , pp. 218-285
    • Tavazoie, S.1    Hughes, J.2    Campbell, M.3
  • 52
    • 47549104748 scopus 로고    scopus 로고
    • Combining guilt-by-Association and guilt-by-profiling to predict saccharomyces cerevisiae gene function
    • Tian, W., Zhang, L.V., Tasan, M., et al. 2008. Combining guilt-by-Association and guilt-by-profiling to predict saccharomyces cerevisiae gene function. Genome Biol. 9, 1-S7
    • (2008) Genome Biol , vol.9
    • Tian, W.1    Zhang, L.V.2    Tasan, M.3
  • 54
    • 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. 2000. Estimating the number of clusters in a data set via the gap statistic. J. R. Statist. Soc. B 63, 411-423
    • (2000) J. R. Statist. Soc , vol.B63 , pp. 411-423
    • Tibshirani, R.1    Walther, G.2    Hastie, T.3
  • 55
    • 0037195138 scopus 로고    scopus 로고
    • Quantitative noise analysis for gene expression microarray experiments
    • Tu, Y., Stolovitzky, G., and Klein, U. 2002. Quantitative noise analysis for gene expression microarray experiments. Proc. Natl. Acade. Sci. 99, 14031-14036
    • (2002) Proc. Natl. Acade. Sci , vol.99 , pp. 14031-14036
    • Tu, Y.1    Stolovitzky, G.2    Klein, U.3
  • 56
    • 0001831117 scopus 로고
    • Mode analysis: A generalization of nearest neighbors which reduces chaining effects
    • Wishart, D. 1969. Mode analysis: A generalization of nearest neighbors which reduces chaining effects. Numer. Taxono. 282-311
    • (1969) Numer. Taxono , pp. 282-311
    • Wishart, D.1
  • 57
    • 0035999974 scopus 로고    scopus 로고
    • Clustering gene expression data using a graph-Theoretic approach: An application of minimum spanning trees
    • Xu, Y., Olman, V., and Xu, D. 2002. Clustering gene expression data using a graph-Theoretic approach: An application of minimum spanning tree. Bioinformatics 19, 536-545. (Pubitemid 34521043)
    • (2002) Bioinformatics , vol.18 , Issue.4 , pp. 536-545
    • Xu, Y.1    Olman, V.2    Xu, D.3
  • 58
    • 0035024021 scopus 로고    scopus 로고
    • Validating clustering for gene expression data
    • Yeung, K.Y., Haynor, D.R., and Ruzzo, W.L. 2001. Validating clustering for gene expression data. Bioinformatics 17, 309-318. (Pubitemid 32421924)
    • (2001) Bioinformatics , vol.17 , Issue.4 , pp. 309-318
    • Yeung, K.Y.1    Haynor, D.R.2    Ruzzo, W.L.3
  • 59
    • 0014976008 scopus 로고
    • Graph-Theoretical methods for detecting and describing gestalt clusters
    • Zahn, C. 1971. Graph-Theoretical methods for detecting and describing gestalt clusters. IEEE Trans. Comput. C20, 68-86
    • (1971) IEEE Trans Comput , vol.C20 , pp. 68-86
    • Zahn, C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.