메뉴 건너뛰기




Volumn 11, Issue SUPPL. 6, 2010, Pages

Time lagged information theoretic approaches to the reverse engineering of gene regulatory networks

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY OF INFORMATION; CONDITIONAL MUTUAL INFORMATION; DYNAMIC BAYESIAN NETWORKS; GENE REGULATORY NETWORKS; INFORMATION-THEORETIC APPROACH; MICROARRAY EXPRESSIONS; MODELS AND ALGORITHMS; PRECISION AND RECALL;

EID: 77957695678     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-19     Document Type: Article
Times cited : (33)

References (28)
  • 1
    • 65249094824 scopus 로고    scopus 로고
    • Analysis of biological networks
    • Wiley-Interscience
    • Björn JH, Schreiber F. Analysis of biological networks. 2008, Wiley-Interscience.
    • (2008)
    • Björn, J.H.1    Schreiber, F.2
  • 2
    • 84889418078 scopus 로고    scopus 로고
    • Biomolecular Networks: Methods and Applications in Systems Biology
    • John Wiley and Sons
    • Chen L, Wang RS, Zhang XS. Biomolecular Networks: Methods and Applications in Systems Biology. 2009, John Wiley and Sons.
    • (2009)
    • Chen, L.1    Wang, R.S.2    Zhang, X.S.3
  • 4
    • 61349180117 scopus 로고    scopus 로고
    • Gene regulatory network inference: Data integration in dynamic models - A review.
    • Hecker M, Lambeck S, Toepfer S, Someren EV, Guthke R. Gene regulatory network inference: Data integration in dynamic models - A review. Bio Systems 2009, 96(1):86-103.
    • (2009) Bio Systems , vol.96 , Issue.1 , pp. 86-103
    • Hecker, M.1    Lambeck, S.2    Toepfer, S.3    Someren, E.V.4    Guthke, R.5
  • 5
    • 34249761849 scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • Heckerman D, Geiger D, Chickering DM. Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning 1995, 20:197-243.
    • (1995) Machine Learning , vol.20 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 6
    • 0002644023 scopus 로고    scopus 로고
    • Algorithms for inferring qualitative models of biological networks.
    • Akutsu T, Miyano S, Kuhara S. Algorithms for inferring qualitative models of biological networks. Pacific Symposium on Biocomputing 2000, 4:17-28.
    • (2000) Pacific Symposium on Biocomputing , vol.4 , pp. 17-28
    • Akutsu, T.1    Miyano, S.2    Kuhara, S.3
  • 8
    • 0014489272 scopus 로고
    • Metabolic stability and epigenesis in randomly constructed genetic nets.
    • 10.1016/0022-5193(69)90015-0, 5803332
    • Kauffman SA. Metabolic stability and epigenesis in randomly constructed genetic nets. J Theor Biol 1969, 22:437-467. 10.1016/0022-5193(69)90015-0, 5803332.
    • (1969) J Theor Biol , vol.22 , pp. 437-467
    • Kauffman, S.A.1
  • 9
    • 0036184629 scopus 로고    scopus 로고
    • Probabilistic Boolean Networks: A rule-based uncertainty model for gene regulatory networks.
    • 10.1093/bioinformatics/18.2.261, 11847074
    • Schmulevich I, Dougherty ER, Kim S, Zhang W. Probabilistic Boolean Networks: A rule-based uncertainty model for gene regulatory networks. Bioinformatics 2002, 18(2):261-274. 10.1093/bioinformatics/18.2.261, 11847074.
    • (2002) Bioinformatics , vol.18 , Issue.2 , pp. 261-274
    • Schmulevich, I.1    Dougherty, E.R.2    Kim, S.3    Zhang, W.4
  • 10
    • 0345983657 scopus 로고    scopus 로고
    • From boolean to probabilistic boolean networks as models of genetic regulatory networks.
    • Shmulevich I, Dougherty ER, Zhang W. From boolean to probabilistic boolean networks as models of genetic regulatory networks. Proceedings of the IEEE 2002, 90(11):1778-1792.
    • (2002) Proceedings of the IEEE , vol.90 , Issue.11 , pp. 1778-1792
    • Shmulevich, I.1    Dougherty, E.R.2    Zhang, W.3
  • 12
    • 33748654580 scopus 로고    scopus 로고
    • Inferring gene regulatory networks from time series data using the minimum description length principle.
    • 10.1093/bioinformatics/btl364, 16845143
    • Zhao W, Serpedin E, Dougherty ER. Inferring gene regulatory networks from time series data using the minimum description length principle. Bioinformatics 2006, 22(17):2129-2135. 10.1093/bioinformatics/btl364, 16845143.
    • (2006) Bioinformatics , vol.22 , Issue.17 , pp. 2129-2135
    • Zhao, W.1    Serpedin, E.2    Dougherty, E.R.3
  • 13
    • 45749124003 scopus 로고    scopus 로고
    • Inference of gene regulatory networks based on a universal minimum description length.
    • Article ID: 482090, 11 pages, 2329739, 18437238
    • Dougherty J, Tabus I, Astola J. Inference of gene regulatory networks based on a universal minimum description length. EURASIP Journal on Bioinformatics and Systems Biology 2008, Article ID: 482090, 11 pages, 2329739, 18437238.
    • (2008) EURASIP Journal on Bioinformatics and Systems Biology
    • Dougherty, J.1    Tabus, I.2    Astola, J.3
  • 14
    • 33947305781 scopus 로고    scopus 로고
    • ARACNE: An algorithm for reconstruction of genetic networks in a mammalian cellular context.
    • 10.1186/1471-2105-7-S1-S7, 1810318, 16723010
    • Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Dalla Favera R, Califano A. ARACNE: An algorithm for reconstruction of genetic networks in a mammalian cellular context. BMC Bioinformatics 2006, 7:S7. 10.1186/1471-2105-7-S1-S7, 1810318, 16723010.
    • (2006) BMC Bioinformatics , vol.7
    • Margolin, A.A.1    Nemenman, I.2    Basso, K.3    Wiggins, C.4    Stolovitzky, G.5    Dalla Favera, R.6    Califano, A.7
  • 15
    • 0031616241 scopus 로고    scopus 로고
    • REVEAL: A general reverse engineering algorithm for inference of genetic network architectures
    • Shoudan L. REVEAL: A general reverse engineering algorithm for inference of genetic network architectures. Pacific Symposium on Biocomputing 1998, 3:18-29.
    • (1998) Pacific Symposium on Biocomputing , vol.3 , pp. 18-29
    • Shoudan, L.1
  • 16
    • 0141879236 scopus 로고    scopus 로고
    • Model Selection and the Principle of Minimum Description Length.
    • Hansen MH, Yu B. Model Selection and the Principle of Minimum Description Length. Journal of the American Statistical Association 2001, 96(454):746-774.
    • (2001) Journal of the American Statistical Association , vol.96 , Issue.454 , pp. 746-774
    • Hansen, M.H.1    Yu, B.2
  • 18
    • 12744261506 scopus 로고    scopus 로고
    • A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data
    • 10.1093/bioinformatics/bth463, 15308537
    • Zou M, Conzen SD. A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data. Bioinformatics 2005, 21(1):71-79. 10.1093/bioinformatics/bth463, 15308537.
    • (2005) Bioinformatics , vol.21 , Issue.1 , pp. 71-79
    • Zou, M.1    Conzen, S.D.2
  • 20
    • 26944457320 scopus 로고    scopus 로고
    • An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset.
    • Zhang X, Baral C, Kim S. An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset. Proceedings of 10th Conference on Artificial Intelligence in Medicine 2005, 524-534.
    • (2005) Proceedings of 10th Conference on Artificial Intelligence in Medicine , pp. 524-534
    • Zhang, X.1    Baral, C.2    Kim, S.3
  • 23
    • 59649110273 scopus 로고    scopus 로고
    • Generating realistic in silico gene networks for performance assessment of reverse engineering methods
    • 10.1089/cmb.2008.09TT, 19183003
    • Marbach D, Schaffter T, Mattiussi C, Floreano D. Generating realistic in silico gene networks for performance assessment of reverse engineering methods. Journal of Computational Biology 2009, 16(2):229-239. 10.1089/cmb.2008.09TT, 19183003.
    • (2009) Journal of Computational Biology , vol.16 , Issue.2 , pp. 229-239
    • Marbach, D.1    Schaffter, T.2    Mattiussi, C.3    Floreano, D.4
  • 24
    • 33947626576 scopus 로고    scopus 로고
    • Inference of Biologically Relevant Gene Influence Networks Using the Directed Information Criterion
    • II-II
    • Rao A, Hero AO, States DJ, Engel JD. Inference of Biologically Relevant Gene Influence Networks Using the Directed Information Criterion. ICASSP Proceedings 2006, 2(II-II).
    • (2006) ICASSP Proceedings , vol.2
    • Rao, A.1    Hero, A.O.2    States, D.J.3    Engel, J.D.4
  • 28
    • 0033982936 scopus 로고    scopus 로고
    • KEGG: Kyoto Encyclopedia of Genes and Genomes.
    • 10.1093/nar/28.1.27, 102409, 10592173
    • Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 2000, 28:27-30. 10.1093/nar/28.1.27, 102409, 10592173.
    • (2000) Nucleic Acids Res , vol.28 , pp. 27-30
    • Kanehisa, M.1    Goto, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.