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Volumn 29, Issue 3, 2008, Pages 232-242

A modified correlation coefficient based similarity measure for clustering time-course gene expression data

Author keywords

Clustering; Modified correlation coefficient; Pearson's correlation coefficient; Similarity; Spearmann's correlation coefficient; Time course gene expression data

Indexed keywords

CLUSTER ANALYSIS; GENE EXPRESSION; HIERARCHICAL SYSTEMS; MICROARRAYS; PATTERN RECOGNITION; TUMORS;

EID: 37049029995     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2007.09.015     Document Type: Article
Times cited : (34)

References (11)
  • 1
    • 16344369007 scopus 로고    scopus 로고
    • Clustering of gene expression data using a local shape-based similarity measure
    • Balasubramaniyan R., Hüllermeier E., Weskamp N., and Kämper J. Clustering of gene expression data using a local shape-based similarity measure. Bioinformatics 21 (2005) 1069-1077
    • (2005) Bioinformatics , vol.21 , pp. 1069-1077
    • Balasubramaniyan, R.1    Hüllermeier, E.2    Weskamp, N.3    Kämper, J.4
  • 3
    • 0037342510 scopus 로고    scopus 로고
    • Comparisons and validation of statistical clustering techniques for microarray gene expression data
    • Datta S., and Datta S. Comparisons and validation of statistical clustering techniques for microarray gene expression data. Bioinformatics 19 (2003) 459-466
    • (2003) Bioinformatics , vol.19 , pp. 459-466
    • Datta, S.1    Datta, S.2
  • 4
    • 21344486796 scopus 로고
    • Confidence interval estimation subject to order restrictions
    • Hwang J., and Peddada S.D. Confidence interval estimation subject to order restrictions. Annals of Statistics 22 (1994) 67-93
    • (1994) Annals of Statistics , vol.22 , pp. 67-93
    • Hwang, J.1    Peddada, S.D.2
  • 5
    • 0032729435 scopus 로고    scopus 로고
    • Exploring expression data: Identification and analysis of coexpressed genes
    • Heyer L.J., Kruglyak S., and Yooseph S. Exploring expression data: Identification and analysis of coexpressed genes. Genome Research 9 (1999) 1106-1115
    • (1999) Genome Research , vol.9 , pp. 1106-1115
    • Heyer, L.J.1    Kruglyak, S.2    Yooseph, S.3
  • 6
    • 0036855903 scopus 로고    scopus 로고
    • Statistical analysis of a small set of time-ordered gene expression data using linear splines
    • Hoon M.J.L., Imoto S., and Miyano S. Statistical analysis of a small set of time-ordered gene expression data using linear splines. Bioinformatics 18 (2002) 1477-1485
    • (2002) Bioinformatics , vol.18 , pp. 1477-1485
    • Hoon, M.J.L.1    Imoto, S.2    Miyano, S.3
  • 8
    • 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 (2003) 474-482
    • (2003) Bioinformatics , vol.19 , pp. 474-482
    • Luan, Y.1    Li, H.2
  • 9
    • 0037620663 scopus 로고    scopus 로고
    • Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference
    • Peddada S.D., Lobenhofer E.K., Li L., Afshari C.A., Weinberg C.R., and Umbach D.M. Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference. Bioinformatics 19 (2003) 834-841
    • (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
  • 10
    • 84950632109 scopus 로고
    • Objective criteria for the evaluation of clustering methods
    • Rand W.M. Objective criteria for the evaluation of clustering methods. Journal of the American Statistical Association 66 (1971) 846-850
    • (1971) Journal of the American Statistical Association , vol.66 , pp. 846-850
    • Rand, W.M.1
  • 11
    • 4944252468 scopus 로고    scopus 로고
    • Using hidden Markov models to analyze gene expression time course data
    • Schliep A., Schonhuth A., and Steinhoff C. Using hidden Markov models to analyze gene expression time course data. Bioinformatics 19 (2003) i255-i263
    • (2003) Bioinformatics , vol.19
    • Schliep, A.1    Schonhuth, A.2    Steinhoff, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.