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Volumn 23, Issue 15, 2007, Pages 1927-1935

Mining co-regulated gene profiles for the detection of functional associations in gene expression data

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPUTER PROGRAM; DOWN REGULATION; FUNCTIONAL GENOMICS; GENE CLUSTER; GENE EXPRESSION PROFILING; GENETIC ANALYSIS; GENETIC IDENTIFICATION; GENETIC REGULATION; GENETIC SCREENING; MICROARRAY ANALYSIS; PRIORITY JOURNAL; UPREGULATION;

EID: 34548131254     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btm276     Document Type: Article
Times cited : (33)

References (32)
  • 1
    • 0001882616 scopus 로고
    • Fast algorithms for mining association rules
    • Agrawal,R. and Srikant,R. (1994) Fast algorithms for mining association rules. In 20th VLDB Cmorence.
    • (1994) 20th VLDB Cmorence
    • Agrawal, R.1    Srikant, R.2
  • 2
    • 0034730140 scopus 로고    scopus 로고
    • Singular value decomposition for genome-wide expression data processing and modeling
    • Alter,O. et al. (2000) Singular value decomposition for genome-wide expression data processing and modeling. Proc. Natl Acad. Sci. USA, 97, 10101-10106.
    • (2000) Proc. Natl Acad. Sci. USA , vol.97 , pp. 10101-10106
    • Alter, O.1
  • 3
    • 0034069495 scopus 로고    scopus 로고
    • Gene ontology: Tool for the unification of biology. The Gene Ontology Consortium
    • Ashburner,M. et al. (2000) Gene ontology: Tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet., 25, 25-29.
    • (2000) Nat. Genet , vol.25 , pp. 25-29
    • Ashburner, M.1
  • 4
    • 33646894725 scopus 로고    scopus 로고
    • BicAT. a biclustering analysis toolbox
    • Barkow,S. et al. (2006) BicAT. a biclustering analysis toolbox. Bioinformatics, 22, 1282-1283.
    • (2006) Bioinformatics , vol.22 , pp. 1282-1283
    • Barkow, S.1
  • 5
    • 0242690489 scopus 로고    scopus 로고
    • Discovering local structure in gene expression data: The order-preserving submatrix problem
    • Ben-Dor,A. et al. (2003) Discovering local structure in gene expression data: The order-preserving submatrix problem. J. Comput. Biol., 10, 373-384.
    • (2003) J. Comput. Biol , vol.10 , pp. 373-384
    • Ben-Dor, A.1
  • 6
    • 0034602774 scopus 로고    scopus 로고
    • Knowledge-based analysis of microarray gene expression data by using support vector machines
    • Brown,M.P. (2000) Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc. Natl Acad. Sci. USA, 97, 262-267.
    • (2000) Proc. Natl Acad. Sci. USA , vol.97 , pp. 262-267
    • Brown, M.P.1
  • 7
    • 33644656960 scopus 로고    scopus 로고
    • Integrated analysis of gene expression by Association Rules Discovery
    • Carmona-Saez,P et al. (2006) Integrated analysis of gene expression by Association Rules Discovery. BMC Bioinformatics, 7, 54.
    • (2006) BMC Bioinformatics , vol.7 , pp. 54
    • Carmona-Saez, P.1
  • 9
    • 0037245822 scopus 로고    scopus 로고
    • Mining gene expression databases for association rules
    • Creighton,C and Hanash,S. (2003) Mining gene expression databases for association rules. Bioinformatics, 19, 79.
    • (2003) Bioinformatics , vol.19 , pp. 79
    • Creighton, C.1    Hanash, S.2
  • 10
    • 0036399459 scopus 로고    scopus 로고
    • Identifying and quantifying sources of variation in microarray data using high-density cDNA membrane arrays
    • Coombes,K.R. et al. (2002) Identifying and quantifying sources of variation in microarray data using high-density cDNA membrane arrays. J. Comput. Biol., 9, 655-669.
    • (2002) J. Comput. Biol , vol.9 , pp. 655-669
    • Coombes, K.R.1
  • 11
    • 0032441150 scopus 로고    scopus 로고
    • Cluster analysis and display of genome-wide expression patterns
    • Eisen,M.B. et al. (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
  • 12
    • 27544508838 scopus 로고    scopus 로고
    • Analyzing microarray data using quantitative association rules
    • ii123-ii129
    • Georgii,E. et al. (2005) Analyzing microarray data using quantitative association rules. Bionformatics, 21, ii123-ii129.
    • (2005) Bionformatics , vol.21
    • Georgii, E.1
  • 14
    • 33750359883 scopus 로고    scopus 로고
    • Frequent pattern discovery without binarization: Mining attribute profiles. PKDD 2006
    • Gyenesei,A. et al. (2006) Frequent pattern discovery without binarization: Mining attribute profiles. PKDD 2006. Lect. Notes Artif. Intell., 4213, 528-535.
    • (2006) Lect. Notes Artif. Intell , vol.4213 , pp. 528-535
    • Gyenesei, A.1
  • 15
    • 0034616930 scopus 로고    scopus 로고
    • Functional discovery via a compendium of expression profiles
    • Hughes,T.R. et al. (2000) Functional discovery via a compendium of expression profiles. Cell, 102, 109-126.
    • (2000) Cell , vol.102 , pp. 109-126
    • Hughes, T.R.1
  • 16
    • 0036699526 scopus 로고    scopus 로고
    • Revealing modular organization in the yeast transcriptional network
    • Ihmels,J. et al. (2002) Revealing modular organization in the yeast transcriptional network. Nat. Genet., 31, 370-377.
    • (2002) Nat. Genet , vol.31 , pp. 370-377
    • Ihmels, J.1
  • 17
    • 8844220454 scopus 로고    scopus 로고
    • Mining gene expression data for positive and negative co-regulated gene clusters
    • Ji,L and Tan,K.L. (2004) Mining gene expression data for positive and negative co-regulated gene clusters. Bioinformatics, 20, 2711-2718.
    • (2004) Bioinformatics , vol.20 , pp. 2711-2718
    • Ji, L.1    Tan, K.L.2
  • 18
    • 33644874819 scopus 로고    scopus 로고
    • From genomics to chemical genomics: New developments in KEGG
    • Kanehisa,M. et al. (2006) From genomics to chemical genomics: New developments in KEGG. Nucleic Acids Res., 34b, D354-D357.
    • (2006) Nucleic Acids Res , vol.34 b
    • Kanehisa, M.1
  • 19
    • 27944474776 scopus 로고    scopus 로고
    • ErmineJ: Tool for functional analysis of gene expression data sets
    • Lee,H.K. et al. (2005) ErmineJ: Tool for functional analysis of gene expression data sets. BMC Bioinformatics, 6, 269.
    • (2005) BMC Bioinformatics , vol.6 , pp. 269
    • Lee, H.K.1
  • 20
    • 0242317346 scopus 로고    scopus 로고
    • Fundamentals of cDNA microarray data analysis
    • Leung,Y.F. and Cavalieri,D. (2003) Fundamentals of cDNA microarray data analysis. Trends Genet., 19, 649-659.
    • (2003) Trends Genet , vol.19 , pp. 649-659
    • Leung, Y.F.1    Cavalieri, D.2
  • 22
    • 84911977993 scopus 로고    scopus 로고
    • Discovering frequent closed itemsets for association rules
    • Pasquier,N. et al. (1999) Discovering frequent closed itemsets for association rules. Lecture Notes in Computer Science, 1540, 398-416.
    • (1999) Lecture Notes in Computer Science , vol.1540 , pp. 398-416
    • Pasquier, N.1
  • 23
    • 33646137384 scopus 로고    scopus 로고
    • A systematic comparison and evaluation of biclustering methods for gene expression data
    • Prelic,A. et al. (2005) A systematic comparison and evaluation of biclustering methods for gene expression data. Bioinformatics, 22, 1122-1129.
    • (2005) Bioinformatics , vol.22 , pp. 1122-1129
    • Prelic, A.1
  • 24
    • 0035375137 scopus 로고    scopus 로고
    • Computational analysis of microarray data
    • Quackenbush,J. (2001) Computational analysis of microarray data. Nat. Genet., 2, 418-427.
    • (2001) Nat. Genet , vol.2 , pp. 418-427
    • Quackenbush, J.1
  • 25
    • 25444468618 scopus 로고    scopus 로고
    • Noise in gene expression: Origins, consequences, and control
    • Raser,J.M. and O'Shea,E.K. (2005) Noise in gene expression: Origins, consequences, and control. Science, 309, 2010-2013.
    • (2005) Science , vol.309 , pp. 2010-2013
    • Raser, J.M.1    O'Shea, E.K.2
  • 26
    • 0033657261 scopus 로고    scopus 로고
    • principal components analisys to summarize microarray experiments: Application to sporulation time series
    • Raychaudhuri,S. (2000) principal components analisys to summarize microarray experiments: Application to sporulation time series. Pac. Symp. Biocomput, 455-466.
    • (2000) Pac. Symp. Biocomput , pp. 455-466
    • Raychaudhuri, S.1
  • 27
    • 0033027794 scopus 로고    scopus 로고
    • Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoetic differentiation
    • Tamayo,P. et al. (1999) Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoetic differentiation. Proc. Natl Acad. Sci. USA, 96, 2907-2912.
    • (1999) Proc. Natl Acad. Sci. USA , vol.96 , pp. 2907-2912
    • Tamayo, P.1
  • 28
    • 0033028596 scopus 로고    scopus 로고
    • Systematic determination of genetic network architecture
    • Tavazoie,S. et al. (1999) Systematic determination of genetic network architecture. Nat. Genet., 22, 281-285.
    • (1999) Nat. Genet , vol.22 , pp. 281-285
    • Tavazoie, S.1
  • 29
    • 0035082045 scopus 로고    scopus 로고
    • Neural network model of gene expression
    • Vohradsky,J. (2001) Neural network model of gene expression. FASEB J. 15, 846-854.
    • (2001) FASEB J , vol.15 , pp. 846-854
    • Vohradsky, J.1
  • 30
    • 25444496949 scopus 로고    scopus 로고
    • Sources of variation in Affymetrix microarray experiments
    • Zakharkin,S.O. et al. (2005) Sources of variation in Affymetrix microarray experiments. BMC Bioinformatics, 6, 214.
    • (2005) BMC Bioinformatics , vol.6 , pp. 214
    • Zakharkin, S.O.1
  • 31
    • 0004107776 scopus 로고    scopus 로고
    • Charm: An efficient algorithm for closed itemset mining
    • Technical report. Rensselaer Polytechnic Institute, Troy, NY
    • Zaki,M.J. and Hsio,C.-J. (1999) Charm: An efficient algorithm for closed itemset mining. Technical report. Rensselaer Polytechnic Institute, Troy, NY.
    • (1999)
    • Zaki, M.J.1    Hsio, C.-J.2
  • 32
    • 33749620002 scopus 로고    scopus 로고
    • Xu,X. et al. (2006) Mining shifting-and-scaling co-regulation patterns on gene expression profiles. Intl. Confl. Data Eng., 00, 89-98.
    • Xu,X. et al. (2006) Mining shifting-and-scaling co-regulation patterns on gene expression profiles. Intl. Confl. Data Eng., 00, 89-98.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.