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Volumn 19, Issue 10, 2003, Pages 1284-1289

A comparison of parametric versus permutation methods with applications to general and temporal microarray gene expression data

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ANALYTIC METHOD; ARTICLE; CONTROLLED STUDY; DNA MICROARRAY; GENE EXPRESSION; GENE MUTATION; GENETIC VARIABILITY; INTERMETHOD COMPARISON; LEUKEMIA CELL; MATHEMATICAL COMPUTING; MEDICAL RESEARCH; PARAMETRIC TEST; PRIORITY JOURNAL; PROBABILITY; SAMPLE SIZE; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL DISTRIBUTION;

EID: 0038494587     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btg155     Document Type: Article
Times cited : (24)

References (13)
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  • 2
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    • Benjamini, Y.1    Hochberg, Y.2
  • 4
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    • TusherV Empirical Bayes analysis of a microarray experiment
    • Efron,B., Tibshirani,R., Storey,J.D. and Tusher,V (2001) Empirical Bayes analysis of a microarray experiment. JASA, 96, 1151-1160.
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    • Li, C.1    Wong, H.W.2
  • 8
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    • Identifying good diagnostic gene groups from gene expression profiles using the concept of emerging patterns
    • Li,J. and Wong,L. (2002) Identifying good diagnostic gene groups from gene expression profiles using the concept of emerging patterns. Bioinformatics, 18, 725-734.
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    • Li, J.1    Wong, L.2
  • 10
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    • On differential variability of expression ratios: Improving statistical inference about gene expression changes from microarrya data
    • Newton,M.A., Kendziorski,C.M., Richmond,C.s., Blatter,F.R. and Tsui,K.W. (2000) On differential variability of expression ratios: improving statistical inference about gene expression changes from microarrya data. J. Comput. Biol., 8, 37-52.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.