메뉴 건너뛰기




Volumn 2003-January, Issue , 2003, Pages 32-36

Efficient mining from heterogeneous data sets for predicting protein-protein interactions

Author keywords

Biological system modeling; Chemicals; Computational biology; Conferences; Data mining; Parameter estimation; Predictive models; Proteins; Stochastic processes; Testing

Indexed keywords

ALGORITHMS; BIOINFORMATICS; BIOLOGICAL SYSTEMS; CHEMICALS; DATA MINING; EXPERT SYSTEMS; MAXIMUM PRINCIPLE; MOLECULAR BIOLOGY; PARAMETER ESTIMATION; RANDOM PROCESSES; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; TESTING;

EID: 50549099057     PISSN: 15294188     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DEXA.2003.1231994     Document Type: Conference Paper
Times cited : (3)

References (12)
  • 1
    • 0032021533 scopus 로고    scopus 로고
    • A hierarchical latent variable model for data visualization
    • C. M. Bishop and M. E. Tipping. A hierarchical latent variable model for data visualization. IEEE Transactions on PAMI, 20(3):281-293, 1998.
    • (1998) IEEE Transactions on PAMI , vol.20 , Issue.3 , pp. 281-293
    • Bishop, C.M.1    Tipping, M.E.2
  • 2
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm
    • A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the EM algorithm. J. R. Statist. Soc. B, 39:1-38, 1977.
    • (1977) J. R. Statist. Soc. B , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 3
    • 0034818212 scopus 로고    scopus 로고
    • Unsupervised learning by probabilistic latent semantic analysis
    • T. Hofmann. Unsupervised learning by probabilistic latent semantic analysis. Machine Learning, 42:177-196, 2001.
    • (2001) Machine Learning , vol.42 , pp. 177-196
    • Hofmann, T.1
  • 5
    • 0035836765 scopus 로고    scopus 로고
    • A comprehensive two-hybrid analysis to explore the yeast protein interactome
    • T. Ito et al. A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl. Acad. Sci., 98(8):4569-4574, 2001.
    • (2001) Proc. Natl. Acad. Sci. , vol.98 , Issue.8 , pp. 4569-4574
    • Ito, T.1
  • 6
    • 0002714543 scopus 로고    scopus 로고
    • Making large-scale SVM learning practical
    • B. Schölkopf, C. Burges, and A. Smola, editors, MIT Press
    • T. Joachims. Making large-scale SVM learning practical. In B. Schölkopf, C. Burges, and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning. MIT Press, 1999.
    • (1999) Advances in Kernel Methods - Support Vector Learning
    • Joachims, T.1
  • 7
    • 0000216534 scopus 로고    scopus 로고
    • Generalizing case frames using a thesaurus and the MDL principle
    • H. Li and N. Abe. Generalizing case frames using a thesaurus and the MDL principle. Computational Linguistics, 24(2):217-244, 1998.
    • (1998) Computational Linguistics , vol.24 , Issue.2 , pp. 217-244
    • Li, H.1    Abe, N.2
  • 8
    • 0030765448 scopus 로고    scopus 로고
    • MIPS: A database for protein sequences, homology data and yeast genome information
    • H. Mewes, K. Albermann, K. Heumann, S. Leibl, and F. Pfeifefer. MIPS: A database for protein sequences, homology data and yeast genome information. Nucleic Acids Res., 25:28-30, 1997.
    • (1997) Nucleic Acids Res. , vol.25 , pp. 28-30
    • Mewes, H.1    Albermann, K.2    Heumann, K.3    Leibl, S.4    Pfeifefer, F.5
  • 9
    • 0036081347 scopus 로고    scopus 로고
    • MIPS: A database for genomes and protein sequences
    • H. W. Mewes et al. MIPS: A database for genomes and protein sequences. Nucl. Acids Res., 30:31-34, 2002.
    • (2002) Nucl. Acids Res. , vol.30 , pp. 31-34
    • Mewes, H.W.1
  • 10
    • 0018015137 scopus 로고
    • Modeling by shortest data description
    • J. Rissanen. Modeling by shortest data description. Automatica, 14:465-471, 1978.
    • (1978) Automatica , vol.14 , pp. 465-471
    • Rissanen, J.1
  • 11
    • 0000487102 scopus 로고    scopus 로고
    • Estimating the support of a high-dimensional distribution
    • B. Schölkopf et al. Estimating the support of a high-dimensional distribution. Neural Computation, 13:1443-1471, 2001.
    • (2001) Neural Computation , vol.13 , pp. 1443-1471
    • Schölkopf, B.1
  • 12
    • 0037161731 scopus 로고    scopus 로고
    • Comparative assessment of large-scale datasets of protein-protein interactions
    • C. von Mering et al. Comparative assessment of large-scale datasets of protein-protein interactions. Nature, 417:399-403, 2002.
    • (2002) Nature , vol.417 , pp. 399-403
    • Von Mering, C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.