참고문헌
- Baldi, P. and Hatfield, G.W. (2002). DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modelings. (Cambrige, UK, Cambridge University Press)
- Bishop, C.M. (1999). Latent variable models. In Learning in Graphical Models, Jordan, M.I.,ed. (Cambrige; The MIT Press), pp.371-403
- Cho, R.J. et al. (1998). A genome-wide transcriptional analysis of the mitotic cell cycle. Mol. Cell 2, 65-73 https://doi.org/10.1016/S1097-2765(00)80114-8
- Cristianini, N. and Shawe-Taylor, J. (2000). An Introduction to Support Vector Machines and Other Kernel-based Learning Methods (Cambridge; Cambridge University Press)
- Dempster, A.P., Laird, N.M., and Rubin, D.B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society B 39, 1-38
- Eisen, M.B., Spellman, P.T., Brown, P.O., and Botstein, D. (1998). Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863-14868 https://doi.org/10.1073/pnas.95.25.14863
- Fowlkes, C., Shan, Q., Belongie, S., and Malik, J. (2002). Extracting global structure from gene expression profiles. In edso, Methods of Microarray Data Analysis II: Papers from CAMDA 01. Lin, S.M. and Johnson, K.F., (Norwell, MA: Kluwer Academic Publishers), pp. 81-90
- Graepel, T., Burger, M., and Obermayer, K. (1998). Self-organizing maps: Generalizations and new optimization techniques. Neurocomputing 21, 173-190 https://doi.org/10.1016/S0925-2312(98)00035-6
- Herwig, R., Poutska, A. J., Muller, C., Bull, C., Lehrach, H., and O' Brien, J. (1999). Large-scale clustering of cDNA-fingerprinting data. Genome Research 9, 1093-1105 https://doi.org/10.1101/gr.9.11.1093
- Hofmann, T. (2000). Learning the similarity of documents: an information-geometric approach to document retrieval and categorization. In Advances in Neural Information Processing Systems 12, 914-920
- Hofmann, T. (2001). Unsupervised learning by probabilistic latent semantic analysis. Machine Learning 42, 177-196 https://doi.org/10.1023/A:1007617005950
- Jaakkola, T. and Haussler, D. (1999). Exploiting generative models in discriminative classifiers. In Advances in Neural Information Processing Systems 11, 487-493
- Kohonen. T. (1997). Self-Organizing Maps (New York: Springer-Verlag)
- Rose, K., Gurewitz, E., and Fox, G. (1990). A deterministic annealing approach to clustering. Pattern Recognition Letters 11, 589-594 https://doi.org/10.1016/0167-8655(90)90010-Y
- Scherf, U. et al. (2000). A gene expression database for the molecular pharmacology of cancer. Nature Genetics 24, 236-244 https://doi.org/10.1038/73439
- Scholkopf, B. and Sm Nola, A.J. (2001). Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. (Cambridge, MA: MIT Press)
- Shamir, R. and Sharan, R. (2002). Algorithmic approaches to clustering gene expression data. In Jiang, T., Smith, T., Xu, Y., and Zhang, M., edso, Current Topics in Computational Biology, Jiang, T., Smith, T., Xu, Y., and Ahang, M., (Cambridge, MA: MIT Press), pp 269-299
- Spellman, P.T. et al. (1998). Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol. BioI. Cell 9, 3273-3297 https://doi.org/10.1091/mbc.9.12.3273
- Tamayo, P., Slonim, D., Mesirov, J., Zhu, Q., Kitareewan, S. Dmitrovsky, E., Lander, E. S., and Golub, T. R. (1999). Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc. Natl. Acad. Sci. USA 96, 2907-2912 https://doi.org/10.1073/pnas.96.6.2907
- Tavazoie, S., Hughes, J.D., Campbell, M.J., Cho, R.J., and Church, G.M. (1999). Systematic determination of genetic network architecture. Nature Genetics 22, 281-285 https://doi.org/10.1038/10343
- Toronen, P., Kolehmainen, M., Wong, G., and Castren, E. (1999). Analysis of gene expression data using self-organizing maps. FEBS Letters 451(2), 142-146 https://doi.org/10.1016/S0014-5793(99)00524-4
- Tsuda, K., Kin, T., and Asai, K. (2002). Marginalized kernels for biological sequences. Bioinformatics 18(SuppI1), S268-S275 https://doi.org/10.1093/bioinformatics/18.suppl_1.S268