메뉴 건너뛰기




Volumn , Issue , 2009, Pages 201-208

A memetic algorithm for gene selection and molecular classification of cancer

Author keywords

Classification; Gene selection; Local search; Memetic algorithm; Specialized crossover

Indexed keywords

ATTRIBUTE SELECTION; COMPUTATIONAL EXPERIMENT; CROSSOVER OPERATOR; GENE SELECTION; LOCAL SEARCH; MEMETIC ALGORITHMS; MICROARRAY DATA; MICROARRAY DATA SETS; MOLECULAR CLASSIFICATION; OPTIMIZATION PROBLEMS; SELECTION PROCESS; SUPERVISED CLASSIFICATION; SVM CLASSIFIERS;

EID: 72749089621     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1569901.1569930     Document Type: Conference Paper
Times cited : (55)

References (28)
  • 1
    • 63149139219 scopus 로고    scopus 로고
    • Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms
    • E. Alba, J. Garcia-Nieto, L. Jourdan, and E.G. Talbi. Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms. In Proceedings of the IEEE CEC'07, pages 284-290, 2007.
    • (2007) Proceedings of the IEEE CEC'07 , pp. 284-290
    • Alba, E.1    Garcia-Nieto, J.2    Jourdan, L.3    Talbi, E.G.4
  • 2
    • 0034598746 scopus 로고    scopus 로고
    • A. Alizadeh, M.B. Eisen, R.E. Davis, C.Ma, I.S. Lossos, A. Rosenwald, J.C. Boldrick, H. Sabet, T. Tran, X. Yu, J.I. Powell, L. Yang, G.E. Marti, T. Moore, J.J. Hudson, L. Lu, D.B. Lewis, R. Tibshirani, G. Sherlock, W.C. Chan, T.C. Greiner, D.D. Weisenburger, J.O. Armitage, R. Warnke, R. Levy, W. Wilson, M.R. Grever, J.C. Byrd, D. Botstein, P.O. Brown, and L.M. Staudt. Distinct types of diffuse large (b)-cell lymphoma identified by gene expression profiling. Nature, 403:503-511, February 2000.
    • A. Alizadeh, M.B. Eisen, R.E. Davis, C.Ma, I.S. Lossos, A. Rosenwald, J.C. Boldrick, H. Sabet, T. Tran, X. Yu, J.I. Powell, L. Yang, G.E. Marti, T. Moore, J.J. Hudson, L. Lu, D.B. Lewis, R. Tibshirani, G. Sherlock, W.C. Chan, T.C. Greiner, D.D. Weisenburger, J.O. Armitage, R. Warnke, R. Levy, W. Wilson, M.R. Grever, J.C. Byrd, D. Botstein, P.O. Brown, and L.M. Staudt. Distinct types of diffuse large (b)-cell lymphoma identified by gene expression profiling. Nature, 403:503-511, February 2000.
  • 3
    • 0033536012 scopus 로고    scopus 로고
    • Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays
    • U. Alon, N. Barkai, D. Notterman, K. Gish, S. Ybarra, D. Mack, and A.J. Levine. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proc. Nat. Acad. Sci. USA., 96:6745-6750, 1999.
    • (1999) Proc. Nat. Acad. Sci. USA , vol.96 , pp. 6745-6750
    • Alon, U.1    Barkai, N.2    Notterman, D.3    Gish, K.4    Ybarra, S.5    Mack, D.6    Levine, A.J.7
  • 4
    • 0037076322 scopus 로고    scopus 로고
    • Selection bias in gene extraction on the basis of microarray gene-expression data
    • C. Ambroise and G. McLachlan. Selection bias in gene extraction on the basis of microarray gene-expression data. Proc. Nat. Acad. Sci. USA, 99(10):6562-6566, 2002.
    • (2002) Proc. Nat. Acad. Sci. USA , vol.99 , Issue.10 , pp. 6562-6566
    • Ambroise, C.1    McLachlan, G.2
  • 5
    • 0026966646 scopus 로고
    • A training algorithm for optimal margin classifiers
    • B. E. Boser, I. Guyon, and V. Vapnik. A training algorithm for optimal margin classifiers. In COLT, pages 144-152, 1992.
    • (1992) COLT , pp. 144-152
    • Boser, B.E.1    Guyon, I.2    Vapnik, V.3
  • 6
    • 1342330535 scopus 로고    scopus 로고
    • Is cross-validation valid for small-sample microarray classification?
    • U. Braga-Neto and E. R. Dougherty. Is cross-validation valid for small-sample microarray classification? Bioinformatics, 20(3):374-380, 2004.
    • (2004) Bioinformatics , vol.20 , Issue.3 , pp. 374-380
    • Braga-Neto, U.1    Dougherty, E.R.2
  • 7
    • 0036489046 scopus 로고    scopus 로고
    • Comparison of discrimination methods for the classification of tumors using gene expression data
    • S. Dudoit, J. Fridlyand, and T. Speed. Comparison of discrimination methods for the classification of tumors using gene expression data. Journal of the American Statistical Association, 97:77-87, 2002.
    • (2002) Journal of the American Statistical Association , vol.97 , pp. 77-87
    • Dudoit, S.1    Fridlyand, J.2    Speed, T.3
  • 8
    • 0033636139 scopus 로고    scopus 로고
    • Support vector machine classification and validation of cancer tissue samples using microarray expression data
    • T. Furey, N. Cristianini, N. Duffy, D. Bednarski, M. Schummer, and D. Haussler. Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics, 16(10):906-914, 2000.
    • (2000) Bioinformatics , vol.16 , Issue.10 , pp. 906-914
    • Furey, T.1    Cristianini, N.2    Duffy, N.3    Bednarski, D.4    Schummer, M.5    Haussler, D.6
  • 11
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • I. Guyon, J. Weston, S. Barnhill, and V. Vapnik. Gene selection for cancer classification using support vector machines. Machine Learning, 46(1-3):389-422, 2002.
    • (2002) Machine Learning , vol.46 , Issue.1-3 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 12
    • 33745768136 scopus 로고    scopus 로고
    • A hybrid GA/SVM approach for gene selection and classification of microarray data
    • Springer
    • E. Bonilla Huerta, B. Duval, and J.K. Hao. A hybrid GA/SVM approach for gene selection and classification of microarray data. In Lecture Notes in Computer Science, 3907: 34-44. Springer, 2006.
    • (2006) Lecture Notes in Computer Science , vol.3907 , pp. 34-44
    • Bonilla Huerta, E.1    Duval, B.2    Hao, J.K.3
  • 13
    • 25444528447 scopus 로고    scopus 로고
    • Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes
    • T. Jirapech-Umpai and J. Stuart Aitken. Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes. BMC Bioinformatics, 6:148, 2005.
    • (2005) BMC Bioinformatics , vol.6 , pp. 148
    • Jirapech-Umpai, T.1    Stuart Aitken, J.2
  • 14
    • 38049058802 scopus 로고    scopus 로고
    • A genetic embedded approach for gene selection and classification of microarray data
    • Springer
    • J.C. Hernandez Hernandez, B. Duval and J.K. Hao. A genetic embedded approach for gene selection and classification of microarray data. Lecture Notes in Computer Science, 4447: 90-101, Springer, 2007.
    • (2007) Lecture Notes in Computer Science , vol.4447 , pp. 90-101
    • Hernandez Hernandez, J.C.1    Duval, B.2    Hao, J.K.3
  • 17
    • 0036139278 scopus 로고    scopus 로고
    • Gene selection for sample classification based on gene expression data: Study of sensitivity to choice of parameters of the GA/KNN method
    • L. Li, C. Weinberg, T. Darden, and L. Pedersen. Gene selection for sample classification based on gene expression data: study of sensitivity to choice of parameters of the GA/KNN method. Bioinformatics, 17(12):1131-1142, 2001.
    • (2001) Bioinformatics , vol.17 , Issue.12 , pp. 1131-1142
    • Li, L.1    Weinberg, C.2    Darden, T.3    Pedersen, L.4
  • 20
    • 13244252329 scopus 로고    scopus 로고
    • A combinational feature selection and ensemble neural network method for classification of gene expression data
    • B. Liu, Q. Cui, T. Jiang, and S. Ma. A combinational feature selection and ensemble neural network method for classification of gene expression data. BMC Bioinformatics, 5(138):1-12, 2004.
    • (2004) BMC Bioinformatics , vol.5 , Issue.138 , pp. 1-12
    • Liu, B.1    Cui, Q.2    Jiang, T.3    Ma, S.4
  • 21
    • 0005386585 scopus 로고    scopus 로고
    • Iterated local search
    • F. Glover and G. Kochenberger Eds, Springer-Verlag
    • H. R. Lourenco, O. Martin and T. Stutzle. Iterated local search. Handbook of Metaheuristics. F. Glover and G. Kochenberger (Eds.), Springer-Verlag, 321-353, 2003.
    • (2003) Handbook of Metaheuristics , pp. 321-353
    • Lourenco, H.R.1    Martin, O.2    Stutzle, T.3
  • 22
    • 24644477601 scopus 로고    scopus 로고
    • Bayesian learning with local support vector machines for cancer classification with gene expression data
    • Springer
    • E. Marchiori and M. Sebag. Bayesian learning with local support vector machines for cancer classification with gene expression data. Lecture Notes in Computer Science, 3449: 74-83, Springer, 2005.
    • (2005) Lecture Notes in Computer Science , vol.3449 , pp. 74-83
    • Marchiori, E.1    Sebag, M.2
  • 23
  • 24
    • 0344872506 scopus 로고    scopus 로고
    • Molecular classification of cancer types from microarray data using the combination of genetic algorithms and support vector machines
    • S. Peng, Q. Xu, X.B. Ling, X. Peng, W. Du, and L.Chen. Molecular classification of cancer types from microarray data using the combination of genetic algorithms and support vector machines. FEBS Letters, 555(2):358-362, 2003.
    • (2003) FEBS Letters , vol.555 , Issue.2 , pp. 358-362
    • Peng, S.1    Xu, Q.2    Ling, X.B.3    Peng, X.4    Du, W.5    Chen, L.6
  • 25
    • 84890447445 scopus 로고    scopus 로고
    • Variable selection using SVM-based criteria
    • A. Rakotomamonjy. Variable selection using SVM-based criteria. Machine Learning Research, 3:1357-1370, 2003.
    • (2003) Machine Learning Research , vol.3 , pp. 1357-1370
    • Rakotomamonjy, A.1
  • 27
    • 44649169939 scopus 로고    scopus 로고
    • Selection for feature gene subset in microarray expression profiles based on a hybrid algorithm using svm and ga. ISPA 2006
    • W. Xiong, C. Zhang, C. Zhou, and Y. Liang. Selection for feature gene subset in microarray expression profiles based on a hybrid algorithm using svm and ga. ISPA 2006 - LNCS, 4331:637-647, 2006.
    • (2006) LNCS , vol.4331 , pp. 637-647
    • Xiong, W.1    Zhang, C.2    Zhou, C.3    Liang, Y.4
  • 28
    • 34250896121 scopus 로고    scopus 로고
    • Markov blanket-embedded genetic algorithm for gene selection
    • Z. Zhu, Y.S. Ong, and M. Dash. Markov blanket-embedded genetic algorithm for gene selection. Pattern Recognition, 40:3236-3248, 2007.
    • (2007) Pattern Recognition , vol.40 , pp. 3236-3248
    • Zhu, Z.1    Ong, Y.S.2    Dash, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.