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      KCI등재후보

      Statistical Analysis for Detecting Differentially Expressed Genes

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      https://www.riss.kr/link?id=A101601182

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      다국어 초록 (Multilingual Abstract)

      A common task in analyzing microarray data is to determine which genes are differentially expressed across two tissue samples, such as normal and tumor tissues, or samples obtained under two experimental conditions. In this paper, we point out a probl...

      A common task in analyzing microarray data is to determine which genes are differentially expressed across two tissue samples, such as normal and tumor tissues, or samples obtained under two experimental conditions. In this paper, we point out a problem with previous method(Zhao and Pan, 2003) of constructing a null and test statistics. We propose resampling approach to construct test statistic as an alternative method. We also present results of simulation data and real data analysis.

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      참고문헌 (Reference)

      1 "The unbalanced modified ranked ordering-set sample sign test" 5 : 163-176, 2003

      2 "Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments" 12 : 111-140, 2002

      3 "Significance analysis of microarrays applied to the ionizing radiation response" 98 : 5116-5121, 2001

      4 "Replicated microarray data" 12 : 21-36, 2002

      5 "Ranking genes with respect to differential expression" 3 (3): 2002

      6 "On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data" 8 : 37-52, 2001

      7 "Numerical Recipes in C The art of Scientific Computing" Press 1992

      8 "Molecular classfification of cancer class discovery and class prediction by gene expression monitoring" 286 : 531-537, 1999

      9 "Modified nonparametric approaches to detecting differentially expressed genes in replicated microarray" 19 : 1046-1054, 2003

      10 "Maximum likelihood estimation from incomplete data via the EM algorithm Journal of Royal Statistical Society" 1-38, 1977

      1 "The unbalanced modified ranked ordering-set sample sign test" 5 : 163-176, 2003

      2 "Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments" 12 : 111-140, 2002

      3 "Significance analysis of microarrays applied to the ionizing radiation response" 98 : 5116-5121, 2001

      4 "Replicated microarray data" 12 : 21-36, 2002

      5 "Ranking genes with respect to differential expression" 3 (3): 2002

      6 "On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data" 8 : 37-52, 2001

      7 "Numerical Recipes in C The art of Scientific Computing" Press 1992

      8 "Molecular classfification of cancer class discovery and class prediction by gene expression monitoring" 286 : 531-537, 1999

      9 "Modified nonparametric approaches to detecting differentially expressed genes in replicated microarray" 19 : 1046-1054, 2003

      10 "Maximum likelihood estimation from incomplete data via the EM algorithm Journal of Royal Statistical Society" 1-38, 1977

      11 "Information theory and an extension of the maximum likelihood principle 2nd International symposium on information theory" 267-281, 1973

      12 "Inference and Applications to clustering" 1988

      13 "Global gene expression profiling in Escherichia coli K12: improved statistical inference from DNA microarray daa using analysis of variance and a Bayesian statistical framework" 276 : 19937-19944, 2001

      14 "Exploring the new world of the genome with DNA microarrays" 33-37, 1999

      15 "Exploring the metabolic and genetic control of gene expression on a genomic scale" 278 : 680-686, 1997

      16 "Estimating the dimensions of a model" 6 : 461-464, 1978

      17 "Empirical Bayes analysis of a microarray experiment" 96 : 1151-1160, 2001

      18 "Array of hope" 21 : 3-4, 1999

      19 "A statistical model for acquired immune deficiency syndrome" 5 : 919-926, 2003

      20 "A comparative Review of Statistical Methods for Discovering Differentially Expressed Genes in Replicated microarray experiments" 12 : 546-554, 2002

      21 "A Mixture model approach to detecting differentially expressed genes with microarray data" Division of Biostatistics 2001

      22 "A Bayesian framework for the analysis of microarry expression data: regularized t-test and statistical inferences of gene changes" 17 : 509-519, 2001

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2026 평가예정 재인증평가 신청대상 (재인증)
      2020-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2017-01-01 평가 등재학술지 유지 (계속평가) KCI등재
      2013-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2008-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2005-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2004-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2002-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 1.26 1.26 1.15
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      1.05 0.98 0.956 0.4
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