메뉴 건너뛰기




Volumn 11, Issue 2, 2009, Pages 253-264

Dealing with missing values in large-scale studies: Microarray data imputation and beyond

Author keywords

Biomarker discovery; Disease classification; Gene expression microarrays; Mass spectrometry proteomics; Missing value imputation; Statistical modelling

Indexed keywords

ALGORITHM; ARTICLE; COMPUTER PROGRAM; GENE EXPRESSION PROFILING; HIGH THROUGHPUT SCREENING; HUMAN; METHODOLOGY; MICROARRAY ANALYSIS; STATISTICAL MODEL; STATISTICS;

EID: 77950949307     PISSN: 14675463     EISSN: 14774054     Source Type: Journal    
DOI: 10.1093/bib/bbp059     Document Type: Article
Times cited : (140)

References (78)
  • 2
    • 33748520872 scopus 로고    scopus 로고
    • Review - a gentle introduction to imputation of missing values
    • Donders AR, van der Heijden GJ, Stijnen T, et al. Review - a gentle introduction to imputation of missing values. J Clin Epidemiol 2006;59:1087-91.
    • (2006) J Clin Epidemiol , vol.59 , pp. 1087-1091
    • Donders, A.R.1    van der Heijden, G.J.2    Stijnen, T.3
  • 3
    • 0030669030 scopus 로고    scopus 로고
    • Exploring the metabolic and genetic control of gene expression on a genomic scale
    • DeRisi JL, Iyer VR, Brown PO. Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 1997;278:680-6.
    • (1997) Science , vol.278 , pp. 680-686
    • DeRisi, J.L.1    Iyer, V.R.2    Brown, P.O.3
  • 4
    • 0031742022 scopus 로고    scopus 로고
    • Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization
    • Spellman PT, Sherlock G, Zhang MQ, et al. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell 1998;9:3273-97.
    • (1998) Mol Biol Cell , vol.9 , pp. 3273-3297
    • Spellman, P.T.1    Sherlock, G.2    Zhang, M.Q.3
  • 5
    • 0034598746 scopus 로고    scopus 로고
    • Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
    • Alizadeh AA, Eisen MB, Davis RE, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000;403:503-11.
    • (2000) Nature , vol.403 , pp. 503-511
    • Alizadeh, A.A.1    Eisen, M.B.2    Davis, R.E.3
  • 6
    • 13244278004 scopus 로고    scopus 로고
    • Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering
    • de Brevern AG, Hazout S, Malpertuy A. Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering. BMC Bioinformatics 2004;5:114.
    • (2004) BMC Bioinformatics , vol.5 , pp. 114
    • de Brevern, A.G.1    Hazout, S.2    Malpertuy, A.3
  • 7
    • 2342426727 scopus 로고    scopus 로고
    • Gaussian mixture clustering and imputation of microarray data
    • Ouyang M, Welsh WJ, Georgopoulos P. Gaussian mixture clustering and imputation of microarray data. Bioinformatics 2004;20:917-23.
    • (2004) Bioinformatics , vol.20 , pp. 917-923
    • Ouyang, M.1    Welsh, W.J.2    Georgopoulos, P.3
  • 8
    • 27944450456 scopus 로고    scopus 로고
    • DNA microarray data imputation and significance analysis of differential expression
    • Jornsten R, Wang HY, Welsh WJ, et al. DNA microarray data imputation and significance analysis of differential expression. Bioinformatics 2005;21:4155-61.
    • (2005) Bioinformatics , vol.21 , pp. 4155-4161
    • Jornsten, R.1    Wang, H.Y.2    Welsh, W.J.3
  • 9
    • 28444441249 scopus 로고    scopus 로고
    • The influence of missing value imputation on detection of differentially expressed genes from microarray data
    • Scheel I, Aldrin M, Glad IK, et al. The influence of missing value imputation on detection of differentially expressed genes from microarray data. Bioinformatics 2005;21:4272-9.
    • (2005) Bioinformatics , vol.21 , pp. 4272-4279
    • Scheel, I.1    Aldrin, M.2    Glad, I.K.3
  • 10
    • 33751358957 scopus 로고    scopus 로고
    • Effects of replacing the unreliable cDNA microarray measurements on the disease classification based on gene expression profiles and functional modules
    • Wang D, Lv Y, Guo Z, et al. Effects of replacing the unreliable cDNA microarray measurements on the disease classification based on gene expression profiles and functional modules. Bioinformatics 2006;22:2883-9.
    • (2006) Bioinformatics , vol.22 , pp. 2883-2889
    • Wang, D.1    Lv, Y.2    Guo, Z.3
  • 11
    • 43849089338 scopus 로고    scopus 로고
    • Classification accuracy based microarray missing value imputation
    • Mandoiu I, Zelikovsky A, (eds). NJ: Wiley-Interscience
    • Shi Y, Cai Z, Lin G. Classification accuracy based microarray missing value imputation. In: Mandoiu I, Zelikovsky A, (eds). Bioinformatics Algorithms:Techniques and Applications. NJ: Wiley-Interscience, 2007;303-28.
    • (2007) Bioinformatics Algorithms:Techniques and Applications , pp. 303-328
    • Shi, Y.1    Cai, Z.2    Lin, G.3
  • 12
    • 61549132604 scopus 로고    scopus 로고
    • How to improve postgenomic knowledge discovery using imputation
    • Article ID 717136
    • Sehgal MS, Gondal I, Dooley LS, et al. How to improve postgenomic knowledge discovery using imputation. EURASIP J Bioinform Syst Biol 2009, Article ID 717136.
    • (2009) EURASIP J Bioinform Syst Biol
    • Sehgal, M.S.1    Gondal, I.2    Dooley, L.S.3
  • 13
    • 67650376526 scopus 로고    scopus 로고
    • Reverse engineering module networks by PSO-RNN hybrid modeling
    • Zhang Y, Xuan J, de los Reyes BG, et al. Reverse engineering module networks by PSO-RNN hybrid modeling. BMC Genomics 2009;10(Suppl 1):S15.
    • (2009) BMC Genomics , vol.10 , Issue.SUPPL 1
    • Zhang, Y.1    Xuan, J.2    de los Reyes, B.G.3
  • 14
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm
    • Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J Royal Stat Soc B 1977;39:1-38.
    • (1977) J Royal Stat Soc B , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 15
    • 0034960264 scopus 로고    scopus 로고
    • Missing value estimation methods for DNA microarrays
    • Troyanskaya O, Cantor M, Sherlock G, et al. Missing value estimation methods for DNA microarrays. Bioinformatics 2001;17:520-5.
    • (2001) Bioinformatics , vol.17 , pp. 520-525
    • Troyanskaya, O.1    Cantor, M.2    Sherlock, G.3
  • 16
    • 0344033642 scopus 로고    scopus 로고
    • Missing-value estimation using linear and non-linear regression with Bayesian gene selection
    • Zhou X, Wang X, Dougherty ER. Missing-value estimation using linear and non-linear regression with Bayesian gene selection. Bioinformatics 2003;19:2302-7.
    • (2003) Bioinformatics , vol.19 , pp. 2302-2307
    • Zhou, X.1    Wang, X.2    Dougherty, E.R.3
  • 17
    • 2342646842 scopus 로고    scopus 로고
    • LSimpute: accurate estimation of missing values in microarray data with least squares methods
    • Bø TH, Dysvik B, Jonassen I. LSimpute: accurate estimation of missing values in microarray data with least squares methods. Nucleic Acids Res 2004;32:e34.
    • (2004) Nucleic Acids Res , vol.32
    • Bø, T.H.1    Dysvik, B.2    Jonassen, I.3
  • 18
    • 19344371607 scopus 로고    scopus 로고
    • Evaluation of missing value estimation for microarray data
    • Nguyen DV, Wang N, Carroll RJ. Evaluation of missing value estimation for microarray data. J Data Sci 2004;2: 347-70.
    • (2004) J Data Sci , vol.2 , pp. 347-370
    • Nguyen, D.V.1    Wang, N.2    Carroll, R.J.3
  • 19
    • 33747418958 scopus 로고    scopus 로고
    • Dealing with gene expression missing data
    • Brás LP, Menezes JC. Dealing with gene expression missing data. Syst Biol 2006;153:105-19.
    • (2006) Syst Biol , vol.153 , pp. 105-119
    • Brás, L.P.1    Menezes, J.C.2
  • 20
    • 13444304426 scopus 로고    scopus 로고
    • Missing value estimation for DNA microarray gene expression data: local least squares imputation
    • Kim H, Golub GH, Park H. Missing value estimation for DNA microarray gene expression data: local least squares imputation. Bioinformatics 2005;21:187-98.
    • (2005) Bioinformatics , vol.21 , pp. 187-198
    • Kim, H.1    Golub, G.H.2    Park, H.3
  • 21
    • 33646671261 scopus 로고    scopus 로고
    • A simultaneous reconstruction of missing data in DNA microarray
    • Friedland S, Niknejad A, Chihara L. A simultaneous reconstruction of missing data in DNA microarray. Linear Algebra Appl 2006;416:8-28.
    • (2006) Linear Algebra Appl , vol.416 , pp. 8-28
    • Friedland, S.1    Niknejad, A.2    Chihara, L.3
  • 22
    • 33645037239 scopus 로고    scopus 로고
    • Missing value estimation for DNA microarray gene expression data by support vector regression imputation and orthogonal coding scheme
    • Wang X, Li A, Jiang Z, Feng H. Missing value estimation for DNA microarray gene expression data by support vector regression imputation and orthogonal coding scheme. BMC Bioinformatics 2006;7:32.
    • (2006) BMC Bioinformatics , vol.7 , pp. 32
    • Wang, X.1    Li, A.2    Jiang, Z.3    Feng, H.4
  • 23
    • 0242643743 scopus 로고    scopus 로고
    • A Bayesian missing value estimation method for gene expression profile data
    • Oba S, Sato MA, Takemasa I, et al. A Bayesian missing value estimation method for gene expression profile data. Bioinformatics 2003;19:2088-96.
    • (2003) Bioinformatics , vol.19 , pp. 2088-2096
    • Oba, S.1    Sato, M.A.2    Takemasa, I.3
  • 24
    • 13244298228 scopus 로고    scopus 로고
    • Reuse of imputed data in microarray analysis increases imputation efficiency
    • Kim KY, Kim BJ, Yi GS. Reuse of imputed data in microarray analysis increases imputation efficiency. BMC Bioinformatics 2004;5:160.
    • (2004) BMC Bioinformatics , vol.5 , pp. 160
    • Kim, K.Y.1    Kim, B.J.2    Yi, G.S.3
  • 26
    • 53049097990 scopus 로고    scopus 로고
    • Sequential local least squares imputation estimating missing value of microarray data
    • Zhang X, Song X, Wang H, et al. Sequential local least squares imputation estimating missing value of microarray data. Comput Biol Med 2008;38:1112-20.
    • (2008) Comput Biol Med , vol.38 , pp. 1112-1120
    • Zhang, X.1    Song, X.2    Wang, H.3
  • 27
    • 33750989656 scopus 로고    scopus 로고
    • Iterated local least squares microarray missing value imputation
    • Cai Z, Heydari M, Lin G. Iterated local least squares microarray missing value imputation. J Bioinform Comput Biol 2006; 4:935-57.
    • (2006) J Bioinform Comput Biol , vol.4 , pp. 935-957
    • Cai, Z.1    Heydari, M.2    Lin, G.3
  • 28
    • 34248557635 scopus 로고    scopus 로고
    • Improving cluster-based missing value estimation of DNA microarray data
    • Brás LP, Menezes JC. Improving cluster-based missing value estimation of DNA microarray data. Biomol Eng 2007;24: 273-82.
    • (2007) Biomol Eng , vol.24 , pp. 273-282
    • Brás, L.P.1    Menezes, J.C.2
  • 29
    • 19644375092 scopus 로고    scopus 로고
    • Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data
    • Sehgal MS, Gondal I, Dooley LS. Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data. Bioinformatics 2005;21: 2417-23.
    • (2005) Bioinformatics , vol.21 , pp. 2417-2423
    • Sehgal, M.S.1    Gondal, I.2    Dooley, L.S.3
  • 30
    • 46649106930 scopus 로고    scopus 로고
    • Ameliorative missing value imputation for robust biological knowledge inference
    • Sehgal MS, Gondal I, Dooley LS, et al. Ameliorative missing value imputation for robust biological knowledge inference. J Biomed Inform 2008;41:499-514.
    • (2008) J Biomed Inform , vol.41 , pp. 499-514
    • Sehgal, M.S.1    Gondal, I.2    Dooley, L.S.3
  • 31
    • 27644570334 scopus 로고    scopus 로고
    • Quality determination and the repair of poor quality spots in array experiments
    • Tom BD, Gilks WR, Brooke-Powell ET, et al. Quality determination and the repair of poor quality spots in array experiments. BMC Bioinformatics 2005;6:234.
    • (2005) BMC Bioinformatics , vol.6 , pp. 234
    • Tom, B.D.1    Gilks, W.R.2    Brooke-Powell, E.T.3
  • 32
    • 33746974277 scopus 로고    scopus 로고
    • Improving missing value imputation of microarray data by using spot quality weights
    • Johansson P, Häkkinen J. Improving missing value imputation of microarray data by using spot quality weights. BMC Bioinformatics 2006;7:306.
    • (2006) BMC Bioinformatics , vol.7 , pp. 306
    • Johansson, P.1    Häkkinen, J.2
  • 33
    • 34249860522 scopus 로고    scopus 로고
    • Robust imputation method for missing values in microarray data
    • Yoon D, Lee EK, Park T. Robust imputation method for missing values in microarray data. BMC Bioinformatics 2007; 8(Suppl 2):S6.
    • (2007) BMC Bioinformatics , vol.8 , Issue.SUPPL 2
    • Yoon, D.1    Lee, E.K.2    Park, T.3
  • 35
    • 0041346457 scopus 로고    scopus 로고
    • Continuous representations of time-series gene expression data
    • Bar-Joseph Z, Gerber GK, Gifford DK, et al. Continuous representations of time-series gene expression data. J Comput Biol 2003;10:341-56.
    • (2003) J Comput Biol , vol.10 , pp. 341-356
    • Bar-Joseph, Z.1    Gerber, G.K.2    Gifford, D.K.3
  • 36
    • 4944252468 scopus 로고    scopus 로고
    • Using hidden Markov models to analyze gene expression time course data
    • Schliep A, Schönhuth A, Steinhoff C. Using hidden Markov models to analyze gene expression time course data. Bioinformatics 2003;19(Suppl 1):i255-63.
    • (2003) Bioinformatics , vol.19 , Issue.SUPPL 1
    • Schliep, A.1    Schönhuth, A.2    Steinhoff, C.3
  • 37
    • 35348851943 scopus 로고    scopus 로고
    • Two-pass imputation algorithm for missing value estimation in gene expression time series
    • Tsiporkova E, Boeva V. Two-pass imputation algorithm for missing value estimation in gene expression time series. J Bioinform Comput Biol 2007;5:1005-22.
    • (2007) J Bioinform Comput Biol , vol.5 , pp. 1005-1022
    • Tsiporkova, E.1    Boeva, V.2
  • 38
    • 63449094790 scopus 로고    scopus 로고
    • Autoregressive-modelbased missing value estimation for DNA microarray time series data
    • Choong MK, Charbit M, Yan H. Autoregressive-modelbased missing value estimation for DNA microarray time series data. IEEE Trans Inf Technol Biomed 2009;13:131-7.
    • (2009) IEEE Trans Inf Technol Biomed , vol.13 , pp. 131-137
    • Choong, M.K.1    Charbit, M.2    Yan, H.3
  • 39
    • 59649119722 scopus 로고    scopus 로고
    • Timing of gene expression responses to environmental changes
    • Chechik G, Koller D. Timing of gene expression responses to environmental changes. J Comput Biol 2009;16:279-90.
    • (2009) J Comput Biol , vol.16 , pp. 279-290
    • Chechik, G.1    Koller, D.2
  • 40
    • 33644856110 scopus 로고    scopus 로고
    • Improving missing value estimation in microarray data with gene ontology
    • Tuikkala J, Elo L, Nevalainen OS, et al. Improving missing value estimation in microarray data with gene ontology. Bioinformatics 2006;22:566-72.
    • (2006) Bioinformatics , vol.22 , pp. 566-572
    • Tuikkala, J.1    Elo, L.2    Nevalainen, O.S.3
  • 41
    • 77950958687 scopus 로고    scopus 로고
    • Predicting gene expression from combined expression and promoter profile similarity with application to missing value imputation
    • Deutsch A, Brusch L, Byrne H, de Vries G, Herzel H, (eds). Boston: Springer-Birkhäuser
    • Elo LL, Tuikkala J, Nevalainen OS, et al. Predicting gene expression from combined expression and promoter profile similarity with application to missing value imputation. In: Deutsch A, Brusch L, Byrne H, de Vries G, Herzel H, (eds). Mathematical Modeling of Biological Systems; Vol. I. Boston: Springer-Birkhäuser, 2007.
    • (2007) Mathematical Modeling of Biological Systems , vol.1
    • Elo, L.L.1    Tuikkala, J.2    Nevalainen, O.S.3
  • 42
    • 46049116474 scopus 로고    scopus 로고
    • Missing value imputation for microarray gene expression data using histone acetylation information
    • Xiang Q, Dai X, Deng Y, et al. Missing value imputation for microarray gene expression data using histone acetylation information. BMC Bioinformatics 2008;9:252.
    • (2008) BMC Bioinformatics , vol.9 , pp. 252
    • Xiang, Q.1    Dai, X.2    Deng, Y.3
  • 43
    • 33750386831 scopus 로고    scopus 로고
    • Integrative missing value estimation for microarray data
    • Hu J, Li H, Waterman MS, et al. Integrative missing value estimation for microarray data. BMC Bioinformatics 2006;7: 449.
    • (2006) BMC Bioinformatics , vol.7 , pp. 449
    • Hu, J.1    Li, H.2    Waterman, M.S.3
  • 44
    • 34247279367 scopus 로고    scopus 로고
    • A meta-data based method for DNA microarray imputation
    • Jörnsten R, Ouyang M, Wang HY. A meta-data based method for DNA microarray imputation. BMC Bioinformatics 2007;8:109.
    • (2007) BMC Bioinformatics , vol.8 , pp. 109
    • Jörnsten, R.1    Ouyang, M.2    Wang, H.Y.3
  • 45
    • 33645468884 scopus 로고    scopus 로고
    • Microarray missing data imputation based on a set theoretic framework and biological knowledge
    • Gan X, Liew AW, Yan H. Microarray missing data imputation based on a set theoretic framework and biological knowledge. Nucleic Acids Res 2006;34:1608-19.
    • (2006) Nucleic Acids Res , vol.34 , pp. 1608-1619
    • Gan, X.1    Liew, A.W.2    Yan, H.3
  • 46
    • 19344362305 scopus 로고    scopus 로고
    • Prediction of missing values in microarray and use of mixed models to evaluate the predictors
    • Article 10.
    • Feten G, Almøy T, Aastveit AH. Prediction of missing values in microarray and use of mixed models to evaluate the predictors. Stat Appl Genet Mol Biol 2005;4, Article 10.
    • (2005) Stat Appl Genet Mol Biol , vol.4
    • Feten, G.1    Almøy, T.2    Aastveit, A.H.3
  • 47
    • 39749093807 scopus 로고    scopus 로고
    • Which missing value imputation method to use in expression profiles - a comparative study and two selection schemes
    • Brock GN, Shaffer JR, Blakesley RE, et al. Which missing value imputation method to use in expression profiles - a comparative study and two selection schemes. BMC Bioinformatics 2008;9:12.
    • (2008) BMC Bioinformatics , vol.9 , pp. 12
    • Brock, G.N.1    Shaffer, J.R.2    Blakesley, R.E.3
  • 48
    • 43849094303 scopus 로고    scopus 로고
    • Missing value imputation improves clustering and interpretation of gene expression microarray data
    • Tuikkala J, Elo LL, Nevalainen OS, et al. Missing value imputation improves clustering and interpretation of gene expression microarray data. BMC Bioinformatics 2008;9:202.
    • (2008) BMC Bioinformatics , vol.9 , pp. 202
    • Tuikkala, J.1    Elo, L.L.2    Nevalainen, O.S.3
  • 49
    • 77950928117 scopus 로고    scopus 로고
    • BPCA missing value tools. (30 September date last accessed)
    • BPCA missing value tools. http://hawaii.aist-nara.ac.jp/~shige-o/tools/BPCAFill.html (30 September 2009, date last accessed).
    • (2009)
  • 50
    • 77950957037 scopus 로고    scopus 로고
    • arrayImpute - software for exploratory analysis and imputation of missing values for microarray data
    • (27 October date last accessed)
    • Lee EK, Yoon D, Park T. arrayImpute - software for exploratory analysis and imputation of missing values for microarray data. Genomics Informatics 2007;5:129-32. http://bibs.snu.ac.kr/software/arrayImpute (27 October 2009, date last accessed).
    • (2009) Genomics Informatics 2007 , vol.5 , pp. 129-132
    • Lee, E.K.1    Yoon, D.2    Park, T.3
  • 51
    • 77950918698 scopus 로고    scopus 로고
    • LSimpute software supplementary web, page
    • (27 October date last accessed)
    • LSimpute software supplementary web page. http://www.ii.uib.no/~trondb/imputation (27 October 2009, date last accessed).
    • (2009)
  • 52
    • 33645326509 scopus 로고    scopus 로고
    • Comparison of Affymetrix GeneChip expression measures
    • Irizarry RA, Wu Z, Jaffee HA. Comparison of Affymetrix GeneChip expression measures. Bioinformatics 2006;22: 789-94.
    • (2006) Bioinformatics , vol.22 , pp. 789-794
    • Irizarry, R.A.1    Wu, Z.2    Jaffee, H.A.3
  • 53
    • 42549103254 scopus 로고    scopus 로고
    • Significance analysis of microarray for relative quantitation of LC/MS data in proteomics
    • Roxas BA, Li Q. Significance analysis of microarray for relative quantitation of LC/MS data in proteomics. BMC Bioinformatics 2008;9:187.
    • (2008) BMC Bioinformatics , vol.9 , pp. 187
    • Roxas, B.A.1    Li, Q.2
  • 54
    • 68549137863 scopus 로고    scopus 로고
    • A statistical framework for protein quantitation in bottom-up MS-based proteomics
    • Karpievitch Y, Stanley J, Taverner T, et al. A statistical framework for protein quantitation in bottom-up MS-based proteomics. Bioinformatics 2009;25:2028-34.
    • (2009) Bioinformatics , vol.25 , pp. 2028-2034
    • Karpievitch, Y.1    Stanley, J.2    Taverner, T.3
  • 55
    • 67649308408 scopus 로고    scopus 로고
    • Quantitative assessment of tissue biomarkers and construction of a model to predict outcome in breast cancer using multiple imputation
    • Emerson JW, Dolled-Filhart M, Harris L, et al. Quantitative assessment of tissue biomarkers and construction of a model to predict outcome in breast cancer using multiple imputation. Cancer Inform 2009;7:29-40.
    • (2009) Cancer Inform , vol.7 , pp. 29-40
    • Emerson, J.W.1    Dolled-Filhart, M.2    Harris, L.3
  • 56
    • 67650742246 scopus 로고    scopus 로고
    • Integrative analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: a non-linear model to predict abundance of undetected proteins
    • Torres-Garci{dotless}'a W, Zhang W, Runger GC, et al. Integrative analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: a non-linear model to predict abundance of undetected proteins. Bioinformatics 2009;25: 1905-14.
    • (2009) Bioinformatics , vol.25 , pp. 1905-1914
    • Torres-Garci'a, W.1    Zhang, W.2    Runger, G.C.3
  • 57
    • 0035942271 scopus 로고    scopus 로고
    • Significance analysis of microarrays applied to the ionizing radiation response
    • Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 2001;98:5116-21.
    • (2001) Proc Natl Acad Sci USA , vol.98 , pp. 5116-5121
    • Tusher, V.G.1    Tibshirani, R.2    Chu, G.3
  • 58
    • 3242885824 scopus 로고    scopus 로고
    • Expression Profiler: next generation-an online platform for analysis of microarray data
    • Kapushesky M, Kemmeren P, Culhane AC, et al. Expression Profiler: next generation-an online platform for analysis of microarray data. Nucleic Acids Res 2004;32: W465-70.
    • (2004) Nucleic Acids Res , vol.32
    • Kapushesky, M.1    Kemmeren, P.2    Culhane, A.C.3
  • 59
    • 46249116675 scopus 로고    scopus 로고
    • DAnTE: a statistical tool for quantitative analysis of -omics data
    • Polpitiya AD, Qian WJ, Jaitly N, et al. DAnTE: a statistical tool for quantitative analysis of -omics data. Bioinformatics 2008;24:1556-8.
    • (2008) Bioinformatics , vol.24 , pp. 1556-1558
    • Polpitiya, A.D.1    Qian, W.J.2    Jaitly, N.3
  • 60
    • 34247586171 scopus 로고    scopus 로고
    • Deciphering protein-protein interactions Part II. Computational methods to predict protein and domain interaction partners
    • Shoemaker BA, Panchenko AR. Deciphering protein-protein interactions. Part II. Computational methods to predict protein and domain interaction partners. PLoS Comput Biol 2007;3:e43.
    • (2007) PLoS Comput Biol , vol.3
    • Shoemaker, B.A.1    Panchenko, A.R.2
  • 61
    • 55249100285 scopus 로고    scopus 로고
    • An optimized predictive strategy for interactome mapping
    • Aryee MJ, Quackenbush J. An optimized predictive strategy for interactome mapping. J Proteome Res 2008;7:4089-94.
    • (2008) J Proteome Res , vol.7 , pp. 4089-4094
    • Aryee, M.J.1    Quackenbush, J.2
  • 62
    • 58149234807 scopus 로고    scopus 로고
    • Cost-effective strategies for completing the interactome
    • Schwartz AS, Yu J, Gardenour KR, et al. Cost-effective strategies for completing the interactome. Nat Methods 2009;6:55-61.
    • (2009) Nat Methods , vol.6 , pp. 55-61
    • Schwartz, A.S.1    Yu, J.2    Gardenour, K.R.3
  • 63
    • 58149345887 scopus 로고    scopus 로고
    • Practical aspects of imputation-driven meta-analysis of genome-wide association studies
    • de Bakker PI, Ferreira MA, Jia X, et al. Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum Mol Genet 2008;17:R122-8.
    • (2008) Hum Mol Genet , vol.17
    • de Bakker, P.I.1    Ferreira, M.A.2    Jia, X.3
  • 64
    • 64349091037 scopus 로고    scopus 로고
    • SNP imputation in association studies
    • Halperin E, Stephan DA. SNP imputation in association studies. Nat Biotechnol 2009;27:349-51.
    • (2009) Nat Biotechnol , vol.27 , pp. 349-351
    • Halperin, E.1    Stephan, D.A.2
  • 65
    • 60549116311 scopus 로고    scopus 로고
    • A comprehensive evaluation of SNP genotype imputation
    • Nothnagel M, Ellinghaus D, Schreiber S, et al. A comprehensive evaluation of SNP genotype imputation. Hum Genet 2009;125:163-71.
    • (2009) Hum Genet , vol.125 , pp. 163-171
    • Nothnagel, M.1    Ellinghaus, D.2    Schreiber, S.3
  • 66
    • 40549129023 scopus 로고    scopus 로고
    • Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data
    • Ritz C, Edén P. Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data. BMC Genomics 2008;9:25.
    • (2008) BMC Genomics , vol.9 , pp. 25
    • Ritz, C.1    Edén, P.2
  • 67
    • 0344824414 scopus 로고    scopus 로고
    • Robust singular value decomposition analysis of microarray data
    • Liu L, Hawkins DM, Ghosh S, et al. Robust singular value decomposition analysis of microarray data. Proc Natl Acad Sci USA 2003;100:13167-72.
    • (2003) Proc Natl Acad Sci USA , vol.100 , pp. 13167-13172
    • Liu, L.1    Hawkins, D.M.2    Ghosh, S.3
  • 68
    • 34249847958 scopus 로고    scopus 로고
    • pcaMethods-a bioconductor package providing PCA methods for incomplete data
    • Stacklies W, Redestig H, Scholz M, et al. pcaMethods-a bioconductor package providing PCA methods for incomplete data. Bioinformatics 2007;23:1164-7.
    • (2007) Bioinformatics , vol.23 , pp. 1164-1167
    • Stacklies, W.1    Redestig, H.2    Scholz, M.3
  • 69
    • 0001551844 scopus 로고
    • Supervised learning from incomplete data via an EM approach
    • Cowan JD, Tesauro G, Alspector J, (eds). San Francisco CA: Morgan Kaufmann Publishers
    • Ghahramani Z, Jordan MI. Supervised learning from incomplete data via an EM approach. In: Cowan JD, Tesauro G, Alspector J, (eds). Advances in Neural Information Processing Systems; Vol. 6. San Francisco, CA: Morgan Kaufmann Publishers, 1994.
    • (1994) Advances in Neural Information Processing Systems , vol.6
    • Ghahramani, Z.1    Jordan, M.I.2
  • 70
    • 66349133214 scopus 로고    scopus 로고
    • Constrained mixture estimation for analysis and robust classification of clinical time series
    • Costa IG, Schönhuth A, Hafemeister C, et al. Constrained mixture estimation for analysis and robust classification of clinical time series. Bioinformatics 2009; 25:i6-14.
    • (2009) Bioinformatics , vol.25
    • Costa, I.G.1    Schönhuth, A.2    Hafemeister, C.3
  • 71
    • 0021518209 scopus 로고
    • Stochastic relaxation Gibbs distributions and the Bayesian restoration of images
    • Geman S, Geman D. Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Trans Pattern AnalMachine Intel 1984;12:609-628.
    • (1984) IEEE Trans Pattern AnalMachine Intel , vol.12 , pp. 609-628
    • Geman, S.1    Geman, D.2
  • 72
    • 84950758368 scopus 로고
    • The calculation of posterior distributions by data augmentation
    • Tanner MA, Wong WH. The calculation of posterior distributions by data augmentation. J Amer Statist Assoc 1987; 82:528-49.
    • (1987) J Amer Statist Assoc , vol.82 , pp. 528-549
    • Tanner, M.A.1    Wong, W.H.2
  • 73
    • 44449136102 scopus 로고    scopus 로고
    • Bayesian biclustering of gene expression data
    • Gu J, Liu JS. Bayesian biclustering of gene expression data. BMC Genomics 2008;9(Suppl 1):S4.
    • (2008) BMC Genomics , vol.9 , Issue.SUPPL 1
    • Gu, J.1    Liu, J.S.2
  • 74
    • 33845882199 scopus 로고    scopus 로고
    • Towards clustering of incomplete microarray data without the use of imputation
    • Kim DW, Lee KY, Lee KH, et al. Towards clustering of incomplete microarray data without the use of imputation. Bioinformatics 2007;23:107-13.
    • (2007) Bioinformatics , vol.23 , pp. 107-113
    • Kim, D.W.1    Lee, K.Y.2    Lee, K.H.3
  • 75
    • 34249744481 scopus 로고    scopus 로고
    • A multi-stage approach to clustering and imputation of gene expression profiles
    • Wong DS, Wong FK, Wood GR. A multi-stage approach to clustering and imputation of gene expression profiles. Bioinformatics 2007;23:998-1005.
    • (2007) Bioinformatics , vol.23 , pp. 998-1005
    • Wong, D.S.1    Wong, F.K.2    Wood, G.R.3
  • 76
    • 34147164582 scopus 로고    scopus 로고
    • An ensemble approach to microarray databased gene prioritization after missing value imputation
    • Hua D, Lai Y. An ensemble approach to microarray databased gene prioritization after missing value imputation. Bioinformatics 2007;23:747-54.
    • (2007) Bioinformatics , vol.23 , pp. 747-754
    • Hua, D.1    Lai, Y.2
  • 77
    • 69249105669 scopus 로고    scopus 로고
    • Optimized detection of differential expression in global profiling experiments: case studies in clinical transcriptomic and quantitative proteomic datasets
    • Elo LL, Hiissa J, Tuimala J, et al. Optimized detection of differential expression in global profiling experiments: case studies in clinical transcriptomic and quantitative proteomic datasets. Brief Bioinform 2009;10:547-55.
    • (2009) Brief Bioinform , vol.10 , pp. 547-555
    • Elo, L.L.1    Hiissa, J.2    Tuimala, J.3
  • 78
    • 70349678392 scopus 로고    scopus 로고
    • Resampling reveals sample-Level differential expression in clinical genomewide studies
    • Hiissa J, Elo LL, Huhtinen K, et al. Resampling reveals sample-Level differential expression in clinical genomewide studies. OMICS - J Integr Biol 2009;13: 381-96.
    • (2009) OMICS - J Integr Biol , vol.13 , pp. 381-396
    • Hiissa, J.1    Elo, L.L.2    Huhtinen, K.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.