메뉴 건너뛰기




Volumn 37, Issue 1, 2015, Pages 41-53

Data fusion by matrix factorization

Author keywords

Bioinformatics; Cheminformatics; Data fusion; Data mining; Intermediate data integration; Matrix factorization

Indexed keywords

BIOINFORMATICS; DATA FUSION; DATA INTEGRATION; DATA MINING; FACTORIZATION;

EID: 84916887227     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2014.2343973     Document Type: Article
Times cited : (186)

References (68)
  • 1
    • 77958192172 scopus 로고    scopus 로고
    • Environment and disease risks
    • S. M. Rappaport and M. T. Smith, "Environment and disease risks," Science, vol. 330, no. 6003, pp. 460-461, 2010.
    • (2010) Science , vol.330 , Issue.6003 , pp. 460-461
    • Rappaport, S.M.1    Smith, M.T.2
  • 6
    • 0036100116 scopus 로고    scopus 로고
    • Learning gene functional classifications from multiple data types
    • P. Pavlidis, J. Cai, J. Weston, and W. S. Noble, "Learning gene functional classifications from multiple data types," J. Comput. Biol., vol. 9, pp. 401-411, 2002.
    • (2002) J. Comput. Biol. , vol.9 , pp. 401-411
    • Pavlidis, P.1    Cai, J.2    Weston, J.3    Noble, W.S.4
  • 7
    • 33747891871 scopus 로고    scopus 로고
    • Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks
    • O. Gevaert, F. De Smet, D. Timmerman, Y. Moreau, and B. De Moor, "Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks," Bioinformat., vol. 22, no. 14, pp. e184-190, 2006.
    • (2006) Bioinformat. , vol.22 , Issue.14 , pp. e184-e190
    • Gevaert, O.1    De Smet, F.2    Timmerman, D.3    Moreau, Y.4    De Moor, B.5
  • 9
    • 84863840685 scopus 로고    scopus 로고
    • Integration of clinical and gene expression data has a synergetic effect on predicting breast cancer outcome
    • M. H. van Vliet, H. M. Horlings, M. J. van de Vijver, M. J. T. Reinders, and L. F. A. Wessels, "Integration of clinical and gene expression data has a synergetic effect on predicting breast cancer outcome," PLoS One, vol. 7, no. 7, p. e40358, 2012.
    • (2012) PLoS One , vol.7 , Issue.7 , pp. e40358
    • Van Vliet, M.H.1    Horlings, H.M.2    Van De Vijver, M.J.3    Reinders, M.J.T.4    Wessels, L.F.A.5
  • 12
    • 83055181835 scopus 로고    scopus 로고
    • Simultaneous clustering of multi-type relational data via symmetric nonnegative matrix tri-factorization
    • H. Wang, H. Huang, and C. H. Q. Ding, "Simultaneous clustering of multi-type relational data via symmetric nonnegative matrix tri-factorization," in Proc. 20th ACM CIKM Int. Conf. Inf. Knowl. Manage., 2011, pp. 279-284.
    • Proc. 20th ACM CIKM Int. Conf. Inf. Knowl. Manage., 2011 , pp. 279-284
    • Wang, H.1    Huang, H.2    Ding, C.H.Q.3
  • 13
    • 0001093042 scopus 로고    scopus 로고
    • Algorithms for non-negative matrix factorization
    • T. K. Leen, T. G. Dietterich, and V. Tresp, Eds., Cambridge, MA, USA: MIT Press
    • D. D. Lee and H. S. Seung, "Algorithms for non-negative matrix factorization," in Advances in Neural Information Processing Systems, T. K. Leen, T. G. Dietterich, and V. Tresp, Eds., Cambridge, MA, USA: MIT Press, 2000, pp. 556-562.
    • (2000) Advances in Neural Information Processing Systems , pp. 556-562
    • Lee, D.D.1    Seung, H.S.2
  • 14
    • 1642529511 scopus 로고    scopus 로고
    • Metagenes and molecular pattern discovery using matrix factorization
    • J.-P. Brunet, P. Tamayo, T. R. Golub, and J. P. Mesirov, "Metagenes and molecular pattern discovery using matrix factorization," Proc. Nat. Acad. Sci. USA, vol. 101, no. 12, pp. 4164-4169, 2004.
    • (2004) Proc. Nat. Acad. Sci. USA , vol.101 , Issue.12 , pp. 4164-4169
    • Brunet, J.-P.1    Tamayo, P.2    Golub, T.R.3    Mesirov, J.P.4
  • 15
    • 56649100783 scopus 로고    scopus 로고
    • Position-dependent motif characterization using non-negative matrix factorization
    • L. N. Hutchins, S. M. Murphy, P. Singh, and J. H. Graber, "Position-dependent motif characterization using non-negative matrix factorization," Bioinformat., vol. 24, no. 23, pp. 2684-2690, 2008.
    • (2008) Bioinformat. , vol.24 , Issue.23 , pp. 2684-2690
    • Hutchins, L.N.1    Murphy, S.M.2    Singh, P.3    Graber, J.H.4
  • 16
    • 24944500827 scopus 로고    scopus 로고
    • Fast algorithm for the solution of large-scale non-negativity-constrained least squares problems
    • M. H. Van Benthem and M. R. Keenan, "Fast algorithm for the solution of large-scale non-negativity-constrained least squares problems," J. Chemometrics, vol. 18, no. 10, pp. 441-450, 2004.
    • (2004) J. Chemometrics , vol.18 , Issue.10 , pp. 441-450
    • Van Benthem, M.H.1    Keenan, M.R.2
  • 18
    • 36749071484 scopus 로고    scopus 로고
    • SVD based initialization: A head start for nonnegative matrix factorization
    • C. Boutsidis and E. Gallopoulos, "SVD based initialization: A head start for nonnegative matrix factorization," Pattern Recognit., vol. 41, no. 4, pp. 1350-1362, 2008.
    • (2008) Pattern Recognit. , vol.41 , Issue.4 , pp. 1350-1362
    • Boutsidis, C.1    Gallopoulos, E.2
  • 21
    • 84860831442 scopus 로고    scopus 로고
    • Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization
    • H. Wang, H. Huang, C. H. Q. Ding, and F. Nie, "Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization," in Res. Comput. Molecular Biol., vol. 7262, pp. 314-325, 2012.
    • (2012) Res. Comput. Molecular Biol. , vol.7262 , pp. 314-325
    • Wang, H.1    Huang, H.2    Ding, C.H.Q.3    Nie, F.4
  • 22
    • 84868152524 scopus 로고    scopus 로고
    • Discovery of multi-dimensional modules by integrative analysis of cancer genomic data
    • S. Zhang, C.-C. Liu, W. Li, H. Shen, P. W. Laird, and X. J. Zhou, "Discovery of multi-dimensional modules by integrative analysis of cancer genomic data," Nucleic Acids Res., vol. 40, no. 19, pp. 9379-9391, 2012.
    • (2012) Nucleic Acids Res. , vol.40 , Issue.19 , pp. 9379-9391
    • Zhang, S.1    Liu, C.-C.2    Li, W.3    Shen, H.4    Laird, P.W.5    Zhou, X.J.6
  • 24
    • 79959448071 scopus 로고    scopus 로고
    • A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules
    • S.-H. Zhang, Q. Li, J. Liu, and X. J. Zhou, "A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules," Bioinformat., vol. 27, no. 13, pp. 401-409, 2011.
    • (2011) Bioinformat. , vol.27 , Issue.13 , pp. 401-409
    • Zhang, S.-H.1    Li, Q.2    Liu, J.3    Zhou, X.J.4
  • 27
    • 84858720748 scopus 로고    scopus 로고
    • Modelling relational data using Bayesian clustered tensor factorization
    • I. Sutskever, "Modelling relational data using Bayesian clustered tensor factorization," in Proc. Adv. Neural Inf. Process. Syst., 2009, pp. 1821-1828.
    • Proc. Adv. Neural Inf. Process. Syst., 2009 , pp. 1821-1828
    • Sutskever, I.1
  • 29
    • 80053444720 scopus 로고    scopus 로고
    • A three-way model for collective learning on multi-relational data
    • M. Nickel, "A three-way model for collective learning on multi-relational data," in Proc. 28th Int. Conf. Mach. Learn., 2011, pp. 809-816.
    • Proc. 28th Int. Conf. Mach. Learn., 2011 , pp. 809-816
    • Nickel, M.1
  • 30
    • 84886485173 scopus 로고    scopus 로고
    • Context-aware tensor decomposition for relation prediction in social networks
    • A. Rettinger, H. Wermser, Y. Huang, and V. Tresp, "Context-aware tensor decomposition for relation prediction in social networks," Social Netw. Anal. Mining, vol. 2, no. 4, pp. 373-385, 2012.
    • (2012) Social Netw. Anal. Mining , vol.2 , Issue.4 , pp. 373-385
    • Rettinger, A.1    Wermser, H.2    Huang, Y.3    Tresp, V.4
  • 31
    • 68649096448 scopus 로고    scopus 로고
    • Tensor decompositions and applications
    • T. G. Kolda and B. W. Bader, "Tensor decompositions and applications," SIAM Rev., vol. 51, no. 3, pp. 455-500, 2009.
    • (2009) SIAM Rev. , vol.51 , Issue.3 , pp. 455-500
    • Kolda, T.G.1    Bader, B.W.2
  • 34
    • 84862653461 scopus 로고    scopus 로고
    • Combining many interaction networks to predict gene function and analyze gene lists
    • S. Mostafavi and Q. Morris, "Combining many interaction networks to predict gene function and analyze gene lists," Proteomics, vol. 12, no. 10, pp. 1687-196, 2012.
    • (2012) Proteomics , vol.12 , Issue.10 , pp. 1687-2196
    • Mostafavi, S.1    Morris, Q.2
  • 35
    • 34547970997 scopus 로고    scopus 로고
    • Spectral clustering and transductive learning with multiple views
    • D. Zhou and C. J. C. Burges, "Spectral clustering and transductive learning with multiple views," in Proc. 24th Int. Conf. Mach. Learn., 2007, pp. 1159-1166.
    • Proc. 24th Int. Conf. Mach. Learn., 2007 , pp. 1159-1166
    • Zhou, D.1    Burges, C.J.C.2
  • 36
    • 55949104732 scopus 로고    scopus 로고
    • Probabilistic approach to detecting dependencies between data sets
    • A. Klami and S. Kaski, "Probabilistic approach to detecting dependencies between data sets," Neurocomput., vol. 72, no. 1-3, pp. 39-46, 2008.
    • (2008) Neurocomput. , vol.72 , Issue.1-3 , pp. 39-46
    • Klami, A.1    Kaski, S.2
  • 37
    • 78649330399 scopus 로고    scopus 로고
    • Generalized spatial dynamic factor models
    • H. F. Lopes, D. Gamerman, and E. Salazar, "Generalized spatial dynamic factor models," Comput. Statist. Data Anal., vol. 55, no. 3, pp. 1319-1330, 2011.
    • (2011) Comput. Statist. Data Anal. , vol.55 , Issue.3 , pp. 1319-1330
    • Lopes, H.F.1    Gamerman, D.2    Salazar, E.3
  • 38
    • 84858727863 scopus 로고    scopus 로고
    • Variational Gaussian-process factor analysis for modeling spatio-temporal data
    • J. Luttinen and A. Ilin, "Variational Gaussian-process factor analysis for modeling spatio-temporal data," in Proc. Adv. Neural Inf. Process. Syst., 2009, pp. 1177-1185.
    • Proc. Adv. Neural Inf. Process. Syst., 2009 , pp. 1177-1185
    • Luttinen, J.1    Ilin, A.2
  • 39
    • 79960944407 scopus 로고    scopus 로고
    • Bayesian inference for genomic data integration reduces misclassification rate in predicting proteinprotein interactions
    • C. Xing and D. B. Dunson, "Bayesian inference for genomic data integration reduces misclassification rate in predicting proteinprotein interactions," PLoS Comput. Biol., vol. 7, no. 7, p. e1002110, 2011.
    • (2011) PLoS Comput. Biol. , vol.7 , Issue.7 , pp. e1002110
    • Xing, C.1    Dunson, D.B.2
  • 40
    • 33644998121 scopus 로고    scopus 로고
    • Active and dynamic information fusion for multisensor systems with dynamic Bayesian networks
    • Y. Zhang and Q. Ji, "Active and dynamic information fusion for multisensor systems with dynamic Bayesian networks," Trans. Syst. Man Cybern. Part B, vol. 36, no. 2, pp. 467-472, 2006.
    • (2006) Trans. Syst. Man Cybern. Part B , vol.36 , Issue.2 , pp. 467-472
    • Zhang, Y.1    Ji, Q.2
  • 41
    • 65349085291 scopus 로고    scopus 로고
    • Global networks of functional coupling in eukaryotes from comprehensive data integration
    • A. Alexeyenko and E. L. L. Sonnhammer, "Global networks of functional coupling in eukaryotes from comprehensive data integration," Genome Res., vol. 19, no. 6, pp. 1107-16, 2009.
    • (2009) Genome Res. , vol.19 , Issue.6 , pp. 1107-1116
    • Alexeyenko, A.1    Sonnhammer, E.L.L.2
  • 43
    • 19344374461 scopus 로고    scopus 로고
    • Self-organizing information fusion and hierarchical knowledge discovery: A new framework using ARTMAP neural networks
    • G. A. Carpenter, S. Martens, and O. J. Ogas, "Self-organizing information fusion and hierarchical knowledge discovery: A new framework using ARTMAP neural networks," Neural Netw., vol. 18, no. 3, pp. 287-295, 2005.
    • (2005) Neural Netw. , vol.18 , Issue.3 , pp. 287-295
    • Carpenter, G.A.1    Martens, S.2    Ogas, O.J.3
  • 44
    • 84875987456 scopus 로고    scopus 로고
    • Integrative analysis using module-guided random forests reveals correlated genetic factors related to mouse weight
    • Z. Chen and W. Zhang, "Integrative analysis using module-guided random forests reveals correlated genetic factors related to mouse weight," PLoS Comput. Biol., vol. 9, no. 3, p. e1002956, 2013.
    • (2013) PLoS Comput. Biol. , vol.9 , Issue.3 , pp. e1002956
    • Chen, Z.1    Zhang, W.2
  • 50
    • 80052213499 scopus 로고    scopus 로고
    • Multiple kernel learning algorithms
    • M. Gönen and E. Alpaydin, "Multiple kernel learning algorithms," J. Mach. Learn. Res., vol. 12, pp. 2211-2268, 2011.
    • (2011) J. Mach. Learn. Res. , vol.12 , pp. 2211-2268
    • Gönen, M.1    Alpaydin, E.2
  • 51
    • 11144352750 scopus 로고    scopus 로고
    • Kernel selection for the support vector machine
    • R. Debnath and H. Takahashi, "Kernel selection for the support vector machine," IEICE Trans., vol. 87-D, no. 12, pp. 2903-2904, 2004.
    • (2004) IEICE Trans. , vol.87 D , Issue.12 , pp. 2903-2904
    • Debnath, R.1    Takahashi, H.2
  • 52
    • 34047104426 scopus 로고    scopus 로고
    • An ensemble-based incremental learning approach to data fusion
    • D. Parikh and R. Polikar, "An ensemble-based incremental learning approach to data fusion," IEEE Trans. Syst., Man, Cybern., Part B, vol. 37, no. 2, pp. 437-450, 2007.
    • (2007) IEEE Trans. Syst., Man, Cybern., Part B , vol.37 , Issue.2 , pp. 437-450
    • Parikh, D.1    Polikar, R.2
  • 53
    • 78049415626 scopus 로고    scopus 로고
    • An integrative multi-network and multi-classifier approach to predict genetic interactions
    • G. Pandey, B. Zhang, A. N. Chang, C. L. Myers, J. Zhu, V. Kumar, and E. E. Schadt, "An integrative multi-network and multi-classifier approach to predict genetic interactions," PLoS Comput. Biol., vol. 6, no. 9, p. e1000928, 2010.
    • (2010) PLoS Comput. Biol. , vol.6 , Issue.9 , pp. e1000928
    • Pandey, G.1    Zhang, B.2    Chang, A.N.3    Myers, C.L.4    Zhu, J.5    Kumar, V.6    Schadt, E.E.7
  • 54
    • 77954207953 scopus 로고    scopus 로고
    • Discovering transcriptional modules by Bayesian data integration
    • R. S. Savage, Z. Ghahramani, J. E. Griffin, B. J. de la Cruz, and D. L. Wild, "Discovering transcriptional modules by Bayesian data integration," Bioinformat., vol. 26, no. 12, pp. i158-i167, 2010.
    • (2010) Bioinformat. , vol.26 , Issue.12 , pp. i158-i167
    • Savage, R.S.1    Ghahramani, Z.2    Griffin, J.E.3    De La Cruz, B.J.4    Wild, D.L.5
  • 55
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L. Breiman, "Random forests," Mach. Learn., vol. 45, no. 1, pp. 5-32, 2001.
    • (2001) Mach. Learn. , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 56
    • 48249110665 scopus 로고    scopus 로고
    • Microarray-based classification and clinical predictors: On combined classifiers and additional predictive value
    • A.-L. Boulesteix, C. Porzelius, and M. Daumer, "Microarray-based classification and clinical predictors: On combined classifiers and additional predictive value," Bioinformat., vol. 24, no. 15, pp. 1698-1706, 2008.
    • (2008) Bioinformat. , vol.24 , Issue.15 , pp. 1698-1706
    • Boulesteix, A.-L.1    Porzelius, C.2    Daumer, M.3
  • 57
    • 44649123652 scopus 로고    scopus 로고
    • Multi-class discriminant kernel learning via convex programming
    • J. Ye, S. Ji, and J. Chen, "Multi-class discriminant kernel learning via convex programming," J. Mach. Learn. Res., vol. 9, pp. 719-758, 2008.
    • (2008) J. Mach. Learn. Res. , vol.9 , pp. 719-758
    • Ye, J.1    Ji, S.2    Chen, J.3
  • 60
    • 84891760956 scopus 로고    scopus 로고
    • Data, information, knowledge and principle: Back to metabolism in kegg
    • M. Kanehisa, S. Goto, Y. Sato, M. Kawashima, M. Furumichi, and M. Tanabe, "Data, information, knowledge and principle: Back to metabolism in kegg," Nucleic Acids Res., vol. 42, no. D1, pp. D199-D205, 2014.
    • (2014) Nucleic Acids Res. , vol.42 , Issue.D1 , pp. D199-D205
    • Kanehisa, M.1    Goto, S.2    Sato, Y.3    Kawashima, M.4    Furumichi, M.5    Tanabe, M.6
  • 65
    • 67849104638 scopus 로고    scopus 로고
    • Pubchem: A public information system for analyzing bioactivities of small molecules
    • Y. Wang, J. Xiao, T. O. Suzek, J. Zhang, J. Wang, and S. H. Bryant, "Pubchem: A public information system for analyzing bioactivities of small molecules," Nucleic Acids Res., vol. 37, no. suppl 2, pp. W623-W633, 2009.
    • (2009) Nucleic Acids Res. , vol.37 , pp. W623-W633
    • Wang, Y.1    Xiao, J.2    Suzek, T.O.3    Zhang, J.4    Wang, J.5    Bryant, S.H.6
  • 68
    • 61649098813 scopus 로고    scopus 로고
    • Asymmetric relationships between proteins shape genome evolution
    • R. A. Notebaart, P. R. Kensche, M. A. Huynen, B. E. Dutilh, "Asymmetric relationships between proteins shape genome evolution," Genome Biol., vol. 10, no. 2, p. R19, 2009.
    • (2009) Genome Biol. , vol.10 , Issue.2 , pp. R19
    • Notebaart, R.A.1    Kensche, P.R.2    Huynen, M.A.3    Dutilh, B.E.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.