메뉴 건너뛰기




Volumn , Issue , 2007, Pages 3862-3869

A guided genetic algorithm for learning gene regulatory networks

Author keywords

[No Author keywords available]

Indexed keywords

CAUSAL MODEL; GENE REGULATORY NETWORKS; MICROARRAY DATA;

EID: 79551671307     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2007.4424974     Document Type: Conference Paper
Times cited : (3)

References (19)
  • 3
    • 0036207347 scopus 로고    scopus 로고
    • Modeling and simulation of genetic regulatory systems: A literature review
    • H. de Jong, "Modeling and simulation of genetic regulatory systems: a literature review," .Journal on Computational Biology, Vol. 9, pp 67-103, 2002.
    • (2002) Journal on Computational Biology , vol.9 , pp. 67-103
    • De Jong, H.1
  • 4
    • 15944361900 scopus 로고    scopus 로고
    • Informative structure priors: Joint learning of dynamic regulatory networks from multiple types of data
    • A. Bernard and A. J. Hartemink, "Informative Structure Priors: Joint Learning of Dynamic Regulatory Networks from Multiple Types of Data," Pacific Symposium on Biocomputing, Vol. 10, 2005.
    • (2005) Pacific Symposium on Biocomputing , vol.10
    • Bernard, A.1    Hartemink, A.J.2
  • 6
    • 34249761849 scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • D. Heckerman, D. Geiger, and D. Chickering, "Learning Bayesian networks: The combination of knowledge and statistical data", MachineLearning, 20(3):197-243, 1995.
    • (1995) MachineLearning , vol.20 , Issue.3 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.3
  • 9
    • 18144442687 scopus 로고    scopus 로고
    • Inferring subnetworks from perturbed expression profiles
    • D. Pe'er, A. Regev, G. Elidan, and N. Friedman, "Inferring Subnetworks from Perturbed Expression Profiles," Bioinformatics, Vol. 17, pp S215-S224, 2002.
    • (2002) Bioinformatics , vol.17
    • Pe'Er, D.1    Regev, A.2    Elidan, G.3    Friedman, N.4
  • 12
    • 0031742022 scopus 로고    scopus 로고
    • Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization
    • P.T. Spellman, G. Sherlock, M.Q. Zhang, V.R. Iyer, K. Anders, M.B. Eisen, P.O. Brown, D. Botstein, B. Futcher, "Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization," Mol Biol Cell,. Vol. 9(12), pp 3273-97, 1998
    • (1998) Mol Biol Cell,. , vol.9 , Issue.12 , pp. 3273-3297
    • Spellman, P.T.1    Sherlock, G.2    Zhang, M.Q.3    Iyer, V.R.4    Anders, K.5    Eisen, M.B.6    Brown, P.O.7    Botstein, D.8    Futcher, B.9
  • 13
    • 0030245966 scopus 로고    scopus 로고
    • Structure learning of Bayesian networks by genetic algorithms: A performance analysis of control parameters
    • P. Larranaga, M. Poza, Y. Yurramendi, R.H. Murga, C.M.H Kuijpers, "Structure learning of Bayesian networks by genetic algorithms: A performance analysis of control parameters", IEEE Trans Pattern Anal Mach Intell, Vol. 18(9): pp. 912-926, 1996.
    • (1996) IEEE Trans Pattern Anal Mach Intell , vol.18 , Issue.9 , pp. 912-926
    • Larranaga, P.1    Poza, M.2    Yurramendi, Y.3    Murga, R.H.4    Kuijpers, C.M.H.5
  • 14
    • 0343665345 scopus 로고    scopus 로고
    • Discovering probabilistic knowledge from databases using evolutionary computation and minimum description length principle
    • Morgan Kaufmann
    • W. Lam, M.L. Wong, K.S Leung, P.S. Ngan, "Discovering probabilistic knowledge from databases using evolutionary computation and minimum description length principle", Proceedings of the geneticprogramming, Morgan Kaufmann, pp. 786-794, 1998.
    • (1998) Proceedings of the Geneticprogramming , pp. 786-794
    • Lam, W.1    Wong, M.L.2    Leung, K.S.3    Ngan, P.S.4
  • 16
    • 12344259602 scopus 로고    scopus 로고
    • Advances to Bayesian network inference for generating causal networks from observational biological data
    • J. Yu, V.A. Smith, P.P. Wang, A.J. Hartemink, and E.D. Jarvis, "Advances to Bayesian network inference for generating causal networks from observational biological data", Bioinform., 20, 3594-3603, 2004.
    • (2004) Bioinform. , vol.20 , pp. 3594-3603
    • Yu, J.1    Smith, V.A.2    Wang, P.P.3    Hartemink, A.J.4    Jarvis, E.D.5
  • 19
    • 0031015401 scopus 로고    scopus 로고
    • The Swi5 transcription factor of Saccharomyces cerevisiae has a role in exit from mitosis through induction of the CDK-inhibitor SICL in telophase
    • J.H Toyn et al, "The Swi5 transcription factor of Saccharomyces cerevisiae has a role in exit from mitosis through induction of the Cdk-inhibitor Sicl in telophase," Genetics, Vol. 145, pp 85-96, 1997.
    • (1997) Genetics , vol.145 , pp. 85-96
    • Toyn, J.H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.