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Volumn 17, Issue 2, 2002, Pages 37-43

Bayesian methods for elucidating genetic regulatory networks

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORK METHODS; GENETIC REGULATORY NETWORKS;

EID: 0036522639     PISSN: 10947167     EISSN: None     Source Type: Journal    
DOI: 10.1109/5254.999218     Document Type: Article
Times cited : (53)

References (12)
  • 1
    • 0003126516 scopus 로고    scopus 로고
    • Fast optimal leaf ordering for hierarchical clustering
    • Z. Bar-Joseph, D.K. Gifford, and T.S. Jaakkola, "Fast Optimal Leaf Ordering for Hierarchical Clustering," Bioinformatics, vol. 17, supplement 1, 2001, pp. S22-S29.
    • (2001) Bioinformatics , vol.17 , Issue.SUPPL. 1
    • Bar-Joseph, Z.1    Gifford, D.K.2    Jaakkola, T.S.3
  • 2
    • 0034598746 scopus 로고    scopus 로고
    • Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
    • 3 Feb.
    • A.A. Alizadeh et al., "Distinct Types of Diffuse Large B-Cell Lymphoma Identified by Gene Expression Profiling," Nature, vol. 403, No. 6,768, 3 Feb. 2000, pp. 503-511.
    • (2000) Nature , vol.403 , Issue.6768 , pp. 503-511
    • Alizadeh, A.A.1
  • 3
    • 0034704248 scopus 로고    scopus 로고
    • Genome-wide location and function of DNA-binding proteins
    • 22 Dec.
    • B. Ren et al., "Genome-Wide Location and Function of DNA-Binding Proteins," Science vol. 290, no. 5,500, 22 Dec. 2000, pp. 2306-2309.
    • (2000) Science , vol.290 , Issue.5500 , pp. 2306-2309
    • Ren, B.1
  • 4
    • 0000782744 scopus 로고    scopus 로고
    • Combining location and expression data for principled discovery of genetic regulatory networks
    • A.J. Hartemink et al., "Combining Location and Expression Data for Principled Discovery of Genetic Regulatory Networks," Proc. Pacific Symp. Biocomputing, vol. 7, 2002; www-smi.stanford.edu/projects/helix/psb02.
    • (2002) Proc. Pacific Symp. Biocomputing , vol.7
    • Hartemink, A.J.1
  • 5
    • 0035221560 scopus 로고    scopus 로고
    • Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks
    • A.J. Hartemink et al., "Using Graphical Models and Genomic Expression Data to Statistically Validate Models of Genetic Regulatory Networks," Proc. Pacific Symp. Biocomputing, vol. 6, 2001, pp. 422-433; www-smi.stanford.edu/projects/helix/psb01.
    • (2001) Proc. Pacific Symp. Biocomputing , vol.6 , pp. 422-433
    • Hartemink, A.J.1
  • 7
    • 18144442687 scopus 로고    scopus 로고
    • Inferring subnetworks from perturbed expression profiles
    • D. Per'er et al., "Inferring Subnetworks from Perturbed Expression Profiles," Bioinformatics, vol. 17, supplement 1, 2001, pp. S215-S224.
    • (2001) Bioinformatics , vol.17 , Issue.SUPPL. 1
    • Per'er, D.1
  • 8
    • 0004158155 scopus 로고    scopus 로고
    • Modeling gene expression data using dynamic Bayesian networks
    • tech. report, Univ. of Calif., Berkeley
    • K. Murphy and S. Mian, "Modeling Gene Expression Data Using Dynamic Bayesian Networks," tech. report, Univ. of Calif., Berkeley, 1999.
    • (1999)
    • Murphy, K.1    Mian, S.2
  • 9
    • 34249761849 scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • D. Heckerman, D. Geiger, and D.M. Chickering, "Learning Bayesian Networks: The Combination of Knowledge and Statistical Data," Machine Learning, vol. 20, no. 3, 1995, pp. 197-243.
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 10
    • 0033330288 scopus 로고    scopus 로고
    • Variational probabilistic inference and the QMR-DT database
    • T.S. Jaakkola and M.I. Jordan, "Variational Probabilistic Inference and the QMR-DT Database," J. Artificial Intelligence Research, vol. 10, 1999, pp. 291-322.
    • (1999) J. Artificial Intelligence Research , vol.10 , pp. 291-322
    • Jaakkola, T.S.1    Jordan, M.I.2
  • 11
    • 85008018096 scopus 로고    scopus 로고
    • Maximum likelihood estimation of optimal scaling factors for expression array normalization
    • A.J. Hartemink, "Maximum Likelihood Estimation of Optimal Scaling Factors for Expression Array Normalization," Proc. Int'l Symp. Biomedical Optics, Jan. 2001.
    • Proc. Int'l Symp. Biomedical Optics, Jan. 2001.
    • Hartemink, A.J.1
  • 12
    • 0023493883 scopus 로고
    • A model fungal gene regulatory mechanism: The GAL genes of saccharomyces cerevisiae
    • M. Johnston, "A Model Fungal Gene Regulatory Mechanism: The GAL Genes of Saccharomyces Cerevisiae," Microbiological Reviews, vol. 51, no. 4, 1987, pp. 458-476.
    • (1987) Microbiological Reviews , vol.51 , Issue.4 , pp. 458-476
    • Johnston, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.