메뉴 건너뛰기




Volumn 21, Issue 10, 2005, Pages 2488-2495

Selective integration of multiple biological data for supervised network inference

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; BAYES THEOREM; COMPUTER ANALYSIS; COMPUTER NETWORK; CONTROLLED STUDY; GENE EXPRESSION; INFORMATION PROCESSING; MATHEMATICAL COMPUTING; NONHUMAN; PHYLOGENY; PRIORITY JOURNAL; PROTEIN DATABASE;

EID: 19544364324     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/bti339     Document Type: Article
Times cited : (55)

References (24)
  • 2
    • 0020183044 scopus 로고
    • Estimation of structured covariance matrices
    • Burg,J.P. et al. (1982) Estimation of structured covariance matrices. Proc. IEEE, 70, 963-974.
    • (1982) Proc. IEEE , vol.70 , pp. 963-974
    • Burg, J.P.1
  • 3
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm
    • Dempster,A.P. et al. (1977) Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc., B, 39, 1-38.
    • (1977) J. R. Stat. Soc., B , vol.39 , pp. 1-38
    • Dempster, A.P.1
  • 4
    • 0032441150 scopus 로고    scopus 로고
    • Cluster analysis and display of genome-wide expression patterns
    • Eisen,M.B. et al. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA. 95, 14863-14968.
    • (1998) Proc. Natl. Acad. Sci. USA , vol.95 , pp. 14863-14968
    • Eisen, M.B.1
  • 5
    • 0842288337 scopus 로고    scopus 로고
    • Inferring cellular networks using probabilistic graphical models
    • Friedman,N. (2004) Inferring cellular networks using probabilistic graphical models. Science, 303, 799-805.
    • (2004) Science , vol.303 , pp. 799-805
    • Friedman, N.1
  • 6
    • 0037447257 scopus 로고    scopus 로고
    • Assessing experimentally derived interaction in a small world
    • Goldberg,D.S. and Roth,F.P. (2003) Assessing experimentally derived interaction in a small world. Proc. Natl Acad. Sci. USA, 100, 4372-4376.
    • (2003) Proc. Natl. Acad. Sci. USA , vol.100 , pp. 4372-4376
    • Goldberg, D.S.1    Roth, F.P.2
  • 7
    • 0001969211 scopus 로고    scopus 로고
    • Use of receiver operating characteristic (ROC) analysis to evaluate sequence matching
    • Gribskov,M. and Robinson,N.L. (1996) Use of receiver operating characteristic (ROC) analysis to evaluate sequence matching. Comput. Chem. 20, 25-33.
    • (1996) Comput. Chem. , vol.20 , pp. 25-33
    • Gribskov, M.1    Robinson, N.L.2
  • 8
    • 0142184341 scopus 로고    scopus 로고
    • Global analysis of protein localization in budding yeast
    • Huh,W.K. et al. (2003) Global analysis of protein localization in budding yeast. Nature, 425, 686-691.
    • (2003) Nature , vol.425 , pp. 686-691
    • Huh, W.K.1
  • 9
    • 0035836765 scopus 로고    scopus 로고
    • A comprehensive two-hybrid analysis to explore the yeast protein interactome
    • Ito,T. et al. (2001) A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl Acad. Sci. USA, 98, 4569-4574.
    • (2001) Proc. Natl. Acad. Sci. USA , vol.98 , pp. 4569-4574
    • Ito, T.1
  • 10
    • 0345863935 scopus 로고    scopus 로고
    • The KEGG resource for deciphering the genome
    • Kanehisa,M. et al. (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res. 1, D277-D280.
    • (2004) Nucleic Acids Res. , vol.1
    • Kanehisa, M.1
  • 11
    • 19544380439 scopus 로고    scopus 로고
    • Protein classification via kernel matrix completion
    • Schölkopf,B., Tsuda,K. and Vert,J.P, (eds), MIT Press, Cambridge, MA
    • Kin,T. et al. (2004) Protein classification via kernel matrix completion. In Schölkopf,B., Tsuda,K. and Vert,J.P, (eds), Kernel Methods in Computational Biology, MIT Press, Cambridge, MA, pp. 261-274.
    • (2004) Kernel Methods in Computational Biology , pp. 261-274
    • Kin, T.1
  • 12
    • 0041775676 scopus 로고    scopus 로고
    • Diffusion kernels on graphs and other discrete structures
    • Sammut,C. and Hoffmann,A.G. (eds), Morgan Kaufmann, San Francisco
    • Kondor,R.I. and Lafferty,J. (2002) Diffusion kernels on graphs and other discrete structures. In Sammut,C. and Hoffmann,A.G. (eds), Machine Learning, Proceedings of the 19th International Conference (ICML 2002), Morgan Kaufmann, San Francisco, pp. 315-322.
    • (2002) Machine Learning, Proceedings of the 19th International Conference (ICML 2002) , pp. 315-322
    • Kondor, R.I.1    Lafferty, J.2
  • 13
    • 8844263749 scopus 로고    scopus 로고
    • A statistical framework for genomic data fusion
    • Lanckriet,G.R.G. et al. (2004) A statistical framework for genomic data fusion. Bioinformatics, 20, 2626-2635.
    • (2004) Bioinformatics , vol.20 , pp. 2626-2635
    • Lanckriet, G.R.G.1
  • 15
    • 0242500972 scopus 로고    scopus 로고
    • Construction of reliable protein-protein interaction networks with a new interaction generality measure
    • Saito,R. et al. (2003) Construction of reliable protein-protein interaction networks with a new interaction generality measure. Bioinformatics, 19, 756-763.
    • (2003) Bioinformatics , vol.19 , pp. 756-763
    • Saito, R.1
  • 17
    • 0001568882 scopus 로고
    • Gaussian Markov distributions over finite graphs
    • Speed,T. and Kiiveri,H. (1986) Gaussian Markov distributions over finite graphs. Ann. Statist., 14, 138-150.
    • (1986) Ann. Statist. , vol.14 , pp. 138-150
    • Speed, T.1    Kiiveri, H.2
  • 18
    • 0031742022 scopus 로고    scopus 로고
    • Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization
    • Spellman,P.T. et al. (1998) Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol. Biol. Cell, 9, 3273-3297.
    • (1998) Mol. Biol. Cell , vol.9 , pp. 3273-3297
    • Spellman, P.T.1
  • 19
    • 19544368196 scopus 로고    scopus 로고
    • Learning kernels from biological networks by maximizing entropy
    • Tsuda,K. and Noble,W.S. (2004) Learning kernels from biological networks by maximizing entropy. Bioinformatics, 20 (Suppl. 1), i326-i333.
    • (2004) Bioinformatics , vol.20 , Issue.SUPPL. 1
    • Tsuda, K.1    Noble, W.S.2
  • 20
    • 2342585524 scopus 로고    scopus 로고
    • The EM algorithm for kernel matrix completion with auxiliary data
    • Tsuda,K. et al. (2003) The EM algorithm for kernel matrix completion with auxiliary data. J. Mach. Learn. Res. 4, 67-81.
    • (2003) J. Mach. Learn. Res. , vol.4 , pp. 67-81
    • Tsuda, K.1
  • 21
    • 0034628508 scopus 로고    scopus 로고
    • A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae
    • Uetz,P. et al. (2000) A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature, 403, 623-627.
    • (2000) Nature , vol.403 , pp. 623-627
    • Uetz, P.1
  • 22
    • 0037161731 scopus 로고    scopus 로고
    • Comparative assessment of large-scale data sets of protein-protein interactions
    • von Mering,C. et al. (2002) Comparative assessment of large-scale data sets of protein-protein interactions. Nature, 417, 399-403.
    • (2002) Nature , vol.417 , pp. 399-403
    • von Mering, C.1
  • 23
    • 0032289422 scopus 로고    scopus 로고
    • Bayesian classification with Gaussian processes
    • Williams,C.K.I. and Barber,D. (1998) Bayesian classification with Gaussian processes. IEEE Trans. PAMI. 20, 1342-1351.
    • (1998) IEEE Trans. PAMI , vol.20 , pp. 1342-1351
    • Williams, C.K.I.1    Barber, D.2
  • 24
    • 19544389868 scopus 로고    scopus 로고
    • Protein network inference from multiple genomic data: A supervised approach
    • Yamanishi,Y. et al. (2004) Protein network inference from multiple genomic data: a supervised approach. Bioinformatics, 20(Suppl. 1), i363-i370.
    • (2004) Bioinformatics , vol.20 , Issue.SUPPL. 1
    • Yamanishi, Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.