Supervised graph inference

Advances in Neural Information Processing Systems

Volumn , Issue , 2005, Pages

  Vert, Jean Philippe ^a   Yamanishi, Yoshihiro ^b  

^a PSL RESEARCH UNIVERSITY   (France)

^b KYOTO UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

OPTIMIZATION;

EUCLIDEAN SPACES; GENOMIC DATA; METABOLIC NETWORK RECONSTRUCTION; OPTIMIZATION PROBLEMS; REPRODUCING KERNEL HILBERT SPACES; SUPERVISED LEARNING PROBLEMS;

INFERENCE ENGINES;

EID: 84898969241     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. R. Jansen, H. Yu, D. Greenbaum, Y. Kluger, N.J. Krogan, S. Chung, A. Emili, M. Snyder, J.F. Greenblatt, and M. Gerstein. A bayesian networks approach for predicting protein-proteininteractions from genomic data. Science, 302(5644), 2003.
2. N. Friedman, M. Linial, I. Nachman, and D. Peer. Using bayesian networks to analyze expression data. Journal of Computational Biology, 7:601-620, 2000.
3. M. Kanehisa. Prediction of higher order functional networks from genomic data. Pharmacogenomics, 2(4):373-385, 2001.
4. A. Doi, H. Matsuno, M. Nagasaki, and S. Miyano. Hybrid petri net representation of gene regulatory network. In Proceedings of PSB 5, pages 341-352, 2000.
5. E.M. Marcotte, M. Pellegrini, H.-L. Ng, D.W. Rice, T.O. Yeates, and D. Eisenberg. Detecting protein function and protein-protein interactions from genome sequences. Science, 285(5428):751-753, 1999.
6. F. Pazos and A. Valencia. Similarity of phylogenetic trees as indicator of protein?protein interaction. Protein Engineering, 9(14):609-614, 2001.
7. J. R. Bock and D. A. Gough. Predicting protein-protein interactions from primary structure. Bioinformatics, 17:455-460, 2001.
8. B. Schrolkopf, K. Tsuda, and J.-P. Vert. Kernel methods in computational biology. MIT Press, 2004.
9. E.P. Xing, A.Y. Ng, M.I. Jordan, and S. Russell. Distance metric learning with application to clustering with side-information. In NIPS 15, pages 505-512. MIT Press, 2003.
10. G. Wahba. Splines Models for Observational Data. Series in Applied Mathematics, Vol. 59, SIAM, Philadelphia, 1990.
11. F. Girosi, M. Jones, and T. Poggio. Regularization theory and neural networks architectures. Neural Computation, 7(2):219-269, 1995.
12. M. Belkin, P. Niyogi, and V. Sindhwani. Manifold regularization: A geometric framework for learning from examples. Technical Report TR-2004-06, University of Chicago, 2004.
13. B. Scholkopf, A. J. Smola, and K.-R. Muller. Kernel principal component analysis. In B. Scholkopf, C. Burges, and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning, pages 327-352. MIT Press, 1999.
14. Y. Weiss. Segmentation using eigenvectors: A unifying view. In Proceedings of the IEEE International Conference on Computer Vision, pages 975-982. IEEE Computer Society, 1999.
15. A. Y. Ng, M. I. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In NIPS 14, pages 849-856, MIT Press, 2002.
16. F. R. Bach and M. I. Jordan. Kernel independent component analysis. Journal of Machine Learning Research, 3:1-48, 2002.
17. J.-P. Vert and M. Kanehisa. Graph-driven features extraction from microarray data using diffusion kernels and kernel CCA. In NIPS 15. MIT Press, 2003.
18. M. Kanehisa, S. Goto, S. Kawashima, and A. Nakaya. The KEGG databases at genomenet. Nucleic Acids Research, 30:42-46, 2002.
19. P. T. Spellman, G. Sherlock, M. Q. Zhang, K. Anders, M. B. Eisen, P. O. Brown, D. Botstein, and B. Futcher. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol. Biol. Cell, 9:3273-3297, 1998.
20. M. Eisen, P. Spellman, P. O. Brown, and D. Botstein. Cluster analysis and display of genomewide expression patterns. PNAS, 95:14863-14868, 1998.
21. M. Pellegrini, E. M. Marcotte, M. J. Thompson, D. Eisenberg, and T. O. Yeates. Assigning protein functions by comparative genome analysis: protein phylogenetic profiles. PNAS, 96(8):4285-4288, 1999.
22. W.K. Huh, J.V. Falco, C. Gerke, A.S. Carroll, R.W. Howson, J.S. Weissman, and E.K. O'Shea. Global analysis of protein localization in budding yeast. Nature, 425:686-691, 2003.
23. Y. Yamanishi, J.-P. Vert, A. Nakaya, and M. Kanehisa. Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis. Bioinformatics, 19:i323-i330, 2003.