메뉴 건너뛰기




Volumn 2, Issue 1, 2009, Pages

A biclustering algorithm based on a Bicluster Enumeration Tree: Application to DNA microarray data

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; AVERAGE SPEARMAN'S RHO; BICLUSTER ENUMERATION TREE; BICLUSTERING ALGORITHM; COMPUTER PROGRAM; CONSTANTS AND COEFFICIENTS; DATA ANALYSIS; DNA MICROARRAY; EVALUATION; GENE CLUSTER; MEAN SQUARED RESIDUE; PARAMETER; PRIORITY JOURNAL;

EID: 76249128966     PISSN: None     EISSN: 17560381     Source Type: Journal    
DOI: 10.1186/1756-0381-2-9     Document Type: Article
Times cited : (80)

References (45)
  • 9
    • 0036012349 scopus 로고    scopus 로고
    • Plaid models for gene expression data
    • Plaid models for gene expression data. L Lazzeroni A Owen, Statistica Sinica 2002 12 61 86
    • (2002) Statistica Sinica , vol.12 , pp. 61-86
    • Lazzeroni, L.1    Owen, A.2
  • 10
    • 0242690489 scopus 로고    scopus 로고
    • Discovering local structure in gene expression data: The order-preserving submatrix problem
    • 10.1089/10665270360688075. 12935334
    • Discovering local structure in gene expression data: the order-preserving submatrix problem. A Ben-Dor B Chor R Karp Z Yakhini, J Comput Biol 2003 10 373 384 10.1089/10665270360688075 12935334
    • (2003) J Comput Biol , vol.10 , pp. 373-384
    • Ben-Dor, A.1    Chor, B.2    Karp, R.3    Yakhini, Z.4
  • 12
    • 33845864692 scopus 로고    scopus 로고
    • Computing the maxim um similarity bi-clusters of gene expression data
    • 10.1093/bioinformatics/btl560. 17090578
    • Computing the maxim um similarity bi-clusters of gene expression data. X Liu L Wang, Bioinformatics 2007 23 1 50 56 10.1093/bioinformatics/btl560 17090578
    • (2007) Bioinformatics , vol.23 , Issue.1 , pp. 50-56
    • Liu, X.1    Wang, L.2
  • 13
    • 44349136914 scopus 로고    scopus 로고
    • Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate visualization
    • 10.1186/1471-2105-9-210. 18433478
    • Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate visualization. K Cheng N Law W Siu A Liew, BMC Bioinformatics 2008 9 210 10.1186/1471-2105-9-210 18433478
    • (2008) BMC Bioinformatics , vol.9 , pp. 210
    • Cheng, K.1    Law, N.2    Siu, W.3    Liew, A.4
  • 14
    • 65349129356 scopus 로고    scopus 로고
    • Discovering biclusters by iteratively sorting with weighted correlation coefficient in gene expression data
    • 10.1007/s11265-007-0121-2
    • Discovering biclusters by iteratively sorting with weighted correlation coefficient in gene expression data. L Teng L Chan, J Signal Process Syst 2008 50 3 267 280 10.1007/s11265-007-0121-2
    • (2008) J Signal Process Syst , vol.50 , Issue.3 , pp. 267-280
    • Teng, L.1    Chan, L.2
  • 15
    • 33646137384 scopus 로고    scopus 로고
    • A systematic comparison and evaluation of biclustering methods for gene expression data
    • 10.1093/bioinformatics/btl060. 16500941
    • A systematic comparison and evaluation of biclustering methods for gene expression data. A Prelic S Bleuler P Zimmermann P Buhlmann W Gruissem L Hennig L Thiele E Zitzler, Bioinformatics 2006 22 9 1122 1129 10.1093/bioinformatics/ btl060 16500941
    • (2006) Bioinformatics , vol.22 , Issue.9 , pp. 1122-1129
    • Prelic, A.1    Bleuler, S.2    Zimmermann, P.3    Buhlmann, P.4    Gruissem, W.5    Hennig, L.6    Thiele, L.7    Zitzler, E.8
  • 16
    • 11244306358 scopus 로고    scopus 로고
    • Discovering statistically significant biclusters in gene expression data
    • 12169541
    • Discovering statistically significant biclusters in gene expression data. A Tanay R Sharan R Shamir, Bioinformatics 2002 18 136 S144 12169541
    • (2002) Bioinformatics , vol.18
    • Tanay, A.1    Sharan, R.2    Shamir, R.3
  • 19
    • 33746098520 scopus 로고    scopus 로고
    • Application of simulated annealing to the biclustering of gene expression data
    • DOI 10.1109/TITB.2006.872073
    • Application of simulated annealing to the biclustering of gene expression data. K Bryan P Cunningham N Bolshakova, IEEE Transactions on Information Technology on Biomedicine 2006 10 3 519 525 10.1109/TITB.2006.872073 (Pubitemid 44194083)
    • (2006) IEEE Transactions on Information Technology in Biomedicine , vol.10 , Issue.3 , pp. 519-525
    • Bryan, K.1    Cunningham, P.2    Bolshakova, N.3
  • 20
    • 60849136919 scopus 로고    scopus 로고
    • Biclustering of gene expression data using reactive greedy randomized adaptive search procedure
    • 10.1186/1471-2105-10-S1-S27. 19208127
    • Biclustering of gene expression data using reactive greedy randomized adaptive search procedure. A Dharan AS Nair, BMC Bioinformatics 2009 10 Suppl 1 27 10.1186/1471-2105-10-S1-S27 19208127
    • (2009) BMC Bioinformatics , vol.10 , Issue.SUPPL 1 , pp. 1927
    • Dharan, A.1    Nair, A.S.2
  • 22
    • 33748417841 scopus 로고    scopus 로고
    • Multi-objective evolutionary biclustering of gene expression data
    • DOI 10.1016/j.patcog.2006.03.003, PII S0031320306000872, Bioinformatics
    • Multi-objective evolutionary biclustering of gene expression data. S Mitra H Banka, Pattern Recognition 2006 2464 2477 10.1016/j.patcog.2006.03.003 (Pubitemid 44344744)
    • (2006) Pattern Recognition , vol.39 , Issue.12 , pp. 2464-2477
    • Mitra, S.1    Banka, H.2
  • 27
  • 28
    • 27544440058 scopus 로고    scopus 로고
    • Shifting and scaling patterns from gene expression data
    • 10.1093/bioinformatics/bti641. 16144809
    • Shifting and scaling patterns from gene expression data. JS Aguilar-Ruiz, Bioinformatics 2005 21 3840 3845 10.1093/bioinformatics/bti641 16144809
    • (2005) Bioinformatics , vol.21 , pp. 3840-3845
    • Aguilar-Ruiz, J.S.1
  • 30
    • 0003471085 scopus 로고    scopus 로고
    • Nonparametrics: Statistical methods based on ranks
    • Englewood Cliffs, NJ: Prentice-Hall
    • Nonparametrics: Statistical Methods Based on Ranks. EL Lehmann HJM D'Abrera, rev. ed Englewood Cliffs, NJ: Prentice-Hall 1998 292 323
    • (1998) Rev. Ed , pp. 292-323
    • Lehmann, E.L.1    D'Abrera, H.J.M.2
  • 33
    • 4544339167 scopus 로고    scopus 로고
    • Defining transcription modules using large-scale gene expression data
    • Defining transcription modules using large-scale gene expression data. S Bergmann J Ihmels N Barkai, Bioinformatics 2004 13 1993 2003
    • (2004) Bioinformatics , vol.13 , pp. 1993-2003
    • Bergmann, S.1    Ihmels, J.2    Barkai, N.3
  • 34
    • 33646894725 scopus 로고    scopus 로고
    • Bicat: A biclustering analysis toolbox
    • 10.1093/bioinformatics/btl099. 16551664
    • Bicat: a biclustering analysis toolbox. S Barkow S Bleuler A Prelic P Zimmermann E Zitzler, Bioinformatics 2006 22 10 1282 1283 10.1093/ bioinformatics/btl099 16551664
    • (2006) Bioinformatics , vol.22 , Issue.10 , pp. 1282-1283
    • Barkow, S.1    Bleuler, S.2    Prelic, A.3    Zimmermann, P.4    Zitzler, E.5
  • 35
    • 34547602344 scopus 로고    scopus 로고
    • Possibilistic approach for biclustering microarray data
    • 10.1016/j.compbiomed.2007.01.005. 17346690
    • Possibilistic approach for biclustering microarray data. C Cano L Adarve J Lápez A Blanco, Computers in Biology and Medicine 2007 37 1426 1436 10.1016/j.compbiomed.2007.01.005 17346690
    • (2007) Computers in Biology and Medicine , vol.37 , pp. 1426-1436
    • Cano, C.1    Adarve, L.2    Lápez, J.3    Blanco, A.4
  • 36
    • 76249097621 scopus 로고    scopus 로고
    • Biclustering of expression data. (supplementary information)
    • Biclustering of expression data. (supplementary information). Y Cheng GM Church, Technical report 2006 http://arep.med.harvard.edu/biclustering
    • (2006) Technical Report
    • Cheng, Y.1    Church, G.M.2
  • 38
    • 55949097825 scopus 로고    scopus 로고
    • Gene expression data analysis using a novel approach to biclustering combining discrete and continuous data
    • 10.1109/TCBB.2007.70251
    • Gene Expression Data Analysis Using a Novel Approach to Biclustering Combining Discrete and Continuous Data. Y Christinat B Wachmann L Zhang, IEEE/ACM Transactions on Computational Biology and Bioinformatics 2008 5 4 583 593 10.1109/TCBB.2007.70251
    • (2008) IEEE/ACM Transactions on Computational Biology and Bioinformatics , vol.5 , Issue.4 , pp. 583-593
    • Christinat, Y.1    Wachmann, B.2    Zhang, L.3
  • 39
    • 0347513219 scopus 로고    scopus 로고
    • Charactering gene sets with FuncAssociate
    • 10.1093/bioinformatics/btg363. 14668247
    • Charactering gene sets with FuncAssociate. GF Berriz OD King B Bryant C Sander P Frederick, Bioinformatics 2003 19 2502 2504 10.1093/bioinformatics/ btg363 14668247
    • (2003) Bioinformatics , vol.19 , pp. 2502-2504
    • Berriz, G.F.1    King, O.D.2    Bryant, B.3    Sander, C.4    Frederick, P.5
  • 40
    • 62949240361 scopus 로고    scopus 로고
    • Combining Pareto-optimal clusters using supervised learning for identifying co-expressed genes
    • 10.1186/1471-2105-10-27. 19154590
    • Combining Pareto-optimal clusters using supervised learning for identifying co-expressed genes. U Maulik A Mukhopadhyay S Bandyopadhyay, BMC Bioinformatics 2009 10 27 10.1186/1471-2105-10-27 19154590
    • (2009) BMC Bioinformatics , vol.10 , pp. 27
    • Maulik, U.1    Mukhopadhyay, A.2    Bandyopadhyay, S.3
  • 41
    • 0037620663 scopus 로고    scopus 로고
    • Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference
    • 10.1093/bioinformatics/btg093. 12724293
    • Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference. SD Peddada EK Lobenhofer L Li CA Afshari CR Weinberg DM Umbach, Bioinformatics 2003 19 834 841 10.1093/bioinformatics/btg093 12724293
    • (2003) Bioinformatics , vol.19 , pp. 834-841
    • Peddada, S.D.1    Lobenhofer, E.K.2    Li, L.3    Afshari, C.A.4    Weinberg, C.R.5    Umbach, D.M.6
  • 42
    • 4944252468 scopus 로고    scopus 로고
    • Using hidden markov models to analyze gene expression time course data
    • 10.1093/bioinformatics/btg1036. 12855468
    • Using hidden Markov models to analyze gene expression time course data. A Schliep A Schonhuth C Steinhoff, Bioinformatics 2003 19 255 i263 10.1093/bioinformatics/btg1036 12855468
    • (2003) Bioinformatics , vol.19
    • Schliep, A.1    Schonhuth, A.2    Steinhoff, C.3
  • 43
    • 0037339264 scopus 로고    scopus 로고
    • Clustering of time-course gene expression data using a mixed-effects model with B-splines
    • 10.1093/bioinformatics/btg014. 12611802
    • Clustering of time-course gene expression data using a mixed-effects model with B-splines. Y Luan H Li, Bioinformatics 2003 19 474 482 10.1093/bioinformatics/btg014 12611802
    • (2003) Bioinformatics , vol.19 , pp. 474-482
    • Luan, Y.1    Li, H.2
  • 44
    • 9944260282 scopus 로고    scopus 로고
    • Improved biclustering of microarray data demonstrated through systematic performance tests
    • 10.1016/j.csda.2004.02.003
    • Improved biclustering of microarray data demonstrated through systematic performance tests. H Turner T Bailey W Krzanowski, Journal of Computational Statistics and Data analysis 2005 48 235 254 10.1016/j.csda.2004.02.003
    • (2005) Journal of Computational Statistics and Data Analysis , vol.48 , pp. 235-254
    • Turner, H.1    Bailey, T.2    Krzanowski, W.3
  • 45
    • 16344369007 scopus 로고    scopus 로고
    • Clustering of gene expression data using a local shape-based similarity measure
    • 10.1093/bioinformatics/bti095. 15513997
    • Clustering of gene expression data using a local shape-based similarity measure. R Balasubramaniyan H llermeier E Weskamp J Kamper, Bioinformatics 2005 21 1069 1077 10.1093/bioinformatics/bti095 15513997
    • (2005) Bioinformatics , vol.21 , pp. 1069-1077
    • Balasubramaniyan, R.1    Llermeier, H.2    Weskamp, E.3    Kamper, J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.