References
- Allen, G., Tibshirani, R. (2010), Transposable Regularized Covariance Models With an Application to Missing Data Imputation, Annals of Applied Statistics, 4, 764–790.
- Cheng, Y., Church, G. (2000), Biclustering of Gene Expression Data, Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology, 8, 93–103.
- Chipman, H., Tibshirani, R. (2005), Hybrid Hierarchical Clustering With Applications to Microarray Data, Biostatistics, 7, 286–301.
- Cho, H., Dhillon, I.S. (2008), Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 5, 385–400.
- Cho, H., Dhillon, I.S., Guan, Y., Sra, S. (2004), Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data, Proceedings of the Fourth SIAM International Conference on Data Mining, pp. 114–125.
- Eisen, M., Spellman, P., Brown, P., Botstein, D. (1998), Cluster Analysis and Display of Genome-Wide Expression Patterns, Proceedings of the National Academy of Sciences of the United States of America, 95, 14863–14868.
- Fraley, C., Raftery, A. (2002), Model-Based Clustering, Discriminant Analysis, and Density Estimation, Journal of the American Statistical Association, 97, 611–631.
- Friedman, J., Hastie, T., Tibshirani, R. (2007), Sparse Inverse Covariance Estimation With the Graphical Lasso, Biostatistics, 9, 432–441.
- Getz, G., Levine, E., Domany, E. (2000), Coupled Two-Way Clustering of Gene Microarray Data, Proceedings of the National Academy of Sciences, 97, 12079–12084.
- Gu, J., Liu, J. (2008), Bayesian Biclustering of Gene Expression Data, BMC Genomics, 9, S4.
- Gupta, A., and Nagar, D. (1999), Matrix Variate Distributions, Boca Raton, FL: CRC Press.
- Hartigan, J.A. (1972), Direct Clustering of a Data Matrix, Journal of the American Statistical Association, 6, 123–129.
- Hastie, T., Tibshirani, R., and Friedman, J. (2009), The Elements of Statistical Learning; Data Mining, Inference and Prediction, New York: Springer Verlag.
- Hochreiter, S., Bodenhofer, U., Heusel, M., Mayr, A., Mitterecker, A., Kasim, A., Khamiakova, T., Sanden, S., Lin, D., Talloen, W., Bijnens, L., Gohlmann, H., Shkedy, Z., Clevert, D. (2010), Fabia: Factor Analysis for Bicluster Acquisition, Bioinformatics, 26, 1520–1527.
- Kaiser, S., Santamaria, R., Khamiakova, T., Sill, M., Theron, R., Quintales, L., and Leisch, F. (2011), Biclust: BiCluster Algorithms. R Package Version 1.0.1. Available at cran.r-project.org/package=biclust.
- Lazzeroni, L., Owen, A. (2002), Plaid Models for Gene Expression Data, Statistica Sinica, 12, 61–86.
- Lee, M., Shen, H., Huang, J., Marron, J. (2010), Biclustering via Sparse Singular Value Decomposition, Biometrics, 66, 1087–1095.
- Liu, Y., Hayes, D., Nobel, A., Marron, J. (2008), Statistical Significance of Clustering for High-Dimension, Low-Sample Size Data, Journal of the American Statistical Association, 103, 1281–1293.
- Madeira, S., Oliveira, A. (2004), Biclustering Algorithms for Biological Data Analysis: A Survey, IEEE Transactions on Computational Biology and Bioinformatics, 1, 24–45.
- Pan, W., Shen, X. (2007), Penalized Model-Based Clustering With Application to Variable Selection, Journal of Machine Learning Research, 8, 1145–1164.
- Prelic, A., Bleuler, S., Zimmermann, P., Wille, A., Buhlmann, P., Gruissem, W., Hennig, L., Thiele, L., Zitzler, E. (2006), A Systematic Comparison and Evaluation of Biclustering Methods for Gene Expression Data, Bioinformatics, 22, 1122–1129.
- Rand, W.M. (1971), Objective Criteria for the Evaluation of Clustering Methods, Journal of the American Statistical Association, 66, 846–850.
- Shabalin, A., Weigman, V., Perou, C., Nobel, A. (2009), Finding Large Average Submatrices in High Dimensional Data, Annals of Applied Statistics, 3, 985–1012.
- Sill, M., and Kaiser, S. (2011), s4vd: Biclustering via Sparse Singular Value Decomposition Incorporating Stability Selection. R Package Version 1.0. Available at cran.r-project.org/web/packages/s4vd.
- Tang, C., Zhang, L., Zhang, A., Ramanathan, M. (2001), Interrelated Two-Way Clustering: An Unsupervised Approach for Gene Expression Data Analysis, Proceedings of 2nd IEEE International Symposium on Bioinformatics and Bioengineering, Bethesda.
- Tibshirani, R. (1996), Regression Shrinkage and Selection via the Lasso, Journal of the Royal Statistical Society, Series B, 58, 267–288.
- Turner, H., Bailey, T., Krzanowski, W. (2005), Improved Biclustering of Microarray Data Demonstrated Through Systematic Performance Tests, Computational Statistics and Data Analysis, 48, 235–254.
- Wang, S., Zhu, J. (2008), Variable Selection for Model-Based High-Dimensional Clustering and Its Application to Microarray Data, Biometrics, 64, 440–448.
- Witten, D., Tibshirani, R. (2009), Covariance-Regularized Regression and Classification for High-Dimensional Problems, Journal of the Royal Statistical Society, Series B, 71, 615–636, PMCID:PMC2806603.
- ——— (2010), A Framework for Feature Selection in Clustering, Journal of the American Statistical Association, 105, 713–726.
- Witten, D., Tibshirani, R., Hastie, T. (2009), A Penalized Matrix Decomposition, With Applications to Sparse Principal Components and Canonical Correlation Analysis, Biostatistics, 10, 515–534.
- Xie, B., Pan, W., Shen, X. (2008), Penalized Model-Based Clustering With Cluster-Specific Diagonal Covariance Matrices and Grouped Variables, Electronic Journal of Statistics, 2, 168–212.
- Zha, H., He, X., Ding, G., Simon, H., Gu, M. (2001), Spectral Relaxation for K-Means Clustering, Neural Information Processing Systems, 14, 1057–1064.