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Volumn , Issue , 2006, Pages 190-195

Modeling multiple time units delayed gene regulatory network using dynamic Bayesian network

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; DATA MINING; GENE EXPRESSION; TIME SERIES; YEAST;

EID: 78449303632     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icdmw.2006.120     Document Type: Conference Paper
Times cited : (32)

References (20)
  • 1
    • 0033655775 scopus 로고    scopus 로고
    • Mutual information relevance networks: Functional genomic clustering using pairwise entropy measurements
    • A. Butte and I. Kohane. Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. Pac Symp Biocomput, pages 418-29, 2000.
    • (2000) Pac Symp Biocomput , pp. 418-429
    • Butte, A.1    Kohane, I.2
  • 3
    • 2442687038 scopus 로고    scopus 로고
    • A mixed integer linear programming (MILP) framework for inferring time delay in gene regulatory networks
    • M.S. Dasika, A. Gupta and C.D. Marans. A mixed integer linear programming (MILP) framework for inferring time delay in gene regulatory networks. Pac Symp Biocomput, 474-85, 2004.
    • (2004) Pac Symp Biocomput , pp. 474-485
    • Dasika, M.S.1    Gupta, A.2    Marans, C.D.3
  • 8
    • 3042738945 scopus 로고    scopus 로고
    • Dynamic Bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data
    • S.Y. Kim , S. Imoto and S. Miyano Dynamic Bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data. Biosystems., 75(1-3):57-65, 2004.
    • (2004) Biosystems , vol.75 , Issue.1-3 , pp. 57-65
    • Kim, S.Y.1    Imoto, S.2    Miyano, S.3
  • 9
    • 0028482006 scopus 로고
    • Learning Bayesian belief networks: An approach based on the MDL principle
    • W. Lam and F. Bacchus Learning Bayesian belief networks: an approach based on the MDL principle. Computational Intelligence., 10(4), 269-293, 1994.
    • (1994) Computational Intelligence , vol.10 , Issue.4 , pp. 269-293
    • Lam, W.1    Bacchus, F.2
  • 10
    • 33644649220 scopus 로고    scopus 로고
    • Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling
    • X. Li, S. Rao, W. Jiang, and C. etc. Li. Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling. BMC Bioinformatics, 7(1):7-26, 2006.
    • (2006) BMC Bioinformatics , vol.7 , Issue.1 , pp. 7-26
    • Li, X.1    Rao, S.2    Jiang, W.3    Li, C.4
  • 12
    • 0344844807 scopus 로고    scopus 로고
    • Modelling regulatory pathways in e.coli from time series expression profiles
    • I.M. Ong, J.D. Glasner, and D. Page. Modelling regulatory pathways in e.coli from time series expression profiles. Bioinformatics, 18:241-248, 2002.
    • (2002) Bioinformatics , vol.18 , pp. 241-248
    • Ong, I.M.1    Glasner, J.D.2    Page, D.3
  • 13
    • 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, 17(1):215-224, 2001.
    • (2001) Bioinformatics , vol.17 , Issue.1 , pp. 215-224
    • Pe'er, D.1    Regev, A.2    Elidan, G.3    Friedman, N.4
  • 14
    • 4143058645 scopus 로고    scopus 로고
    • Gene networks inference using dynamic bayesian networks
    • B.E. Perrin, L. Ralaivola, and A. Mazurie. Gene networks inference using dynamic bayesian networks. Bioinformatics, 19(2):138-148, 2003.
    • (2003) Bioinformatics , vol.19 , Issue.2 , pp. 138-148
    • Perrin, B.E.1    Ralaivola, L.2    Mazurie, A.3
  • 15
    • 0035861975 scopus 로고    scopus 로고
    • Beyond synexpression relationships: Local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions
    • J. Qian, M. Dolled-Filhart, J. Lin, H.Y. Yu and M. Gerstein Beyond synexpression relationships: local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions. J Mol Biol.,314(5):1053-66, 2001.
    • (2001) J Mol Biol , vol.314 , Issue.5 , pp. 1053-1066
    • Qian, J.1    Dolled-Filhart, M.2    Lin, J.3    Yu, H.Y.4    Gerstein, M.5
  • 19
    • 12744261506 scopus 로고    scopus 로고
    • A new dynamic bayesian network (dbn) approach for identifying gene regulatory networks from time course microarray data
    • M. Zou and S.D. Conzen. A new dynamic bayesian network (dbn) approach for identifying gene regulatory networks from time course microarray data. Bioinformatics, 21(1):71-79, 2005.
    • (2005) Bioinformatics , vol.21 , Issue.1 , pp. 71-79
    • Zou, M.1    Conzen, S.D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.