Non-homogeneous dynamic Bayesian networks for continuous data

Article English OPEN
Grzegorczyk, M. ; Husmeier, D. (2011)
  • References (13)
    13 references, page 1 of 2

    Ahmed, A. and Xing, E. P. (2009) Recovering time-varying networks of dependencies in social and biological studies. Proceedings of the National Academy of Sciences, 106, 11878-11883.

    Alabadi, D., Oyama, T., Yanovsky, M. J., Harmon, F. G., Mas, P. and Kay, S. A. (2001) Reciprocal regulation between TOC1 and LHY/CCA1 within the Arabidopsis circadian clock. Science, 293, 880-883.

    Brooks, S. and Gelman, A. (1998) General methods for monitoring convergence of iterative simulations. Journal of Computational and Graphial Statistics, 7, 434-455.

    Grzegorczyk, M. and Husmeier, D. (2009) Non-stationary continuous dynamic Bayesian networks. In Bengio, Y., Schuurmans, D., Lafferty, J., Williams, C. K. I. and Culotta, A. (eds.), Advances in Neural Information Processing Systems (NIPS), volume 22, pp. 682-690.

    Grzegorczyk, M., Husmeier, D., Edwards, K., Ghazal, P. and Millar, A. (2008) Modelling nonstationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler. Bioinformatics, 24, 2071-2078.

    Grzegorczyk, M., Rahnenfu¨hrer, J. and Husmeier, D. (2010) Modelling non-stationary dynamic gene regulatory processes with the BGM model. Computational Statistics. In Press, DOI 10.1007/s00180-010-0201-9.

    Mockler, T., Michael, T., Priest, H., Shen, R., Sullivan, C., Givan, S., McEntee, C., Kay, S. and Chory, J. (2007) The diurnal project: Diurnal and circadian expression profiling, model-based pattern matching and promoter analysis. Cold Spring Harbor Symposia on Quantitative Biology, 72, 353-363.

    Nobile, A. and Fearnside, A. (2007) Bayesian finite mixtures with an unknown number of components: The allocation sampler. Statistics and Computing, 17, 147-162.

    Robinson, J. W. and Hartemink, A. J. (2009) Non-stationary dynamic Bayesian networks. In Koller, D., Schuurmans, D., Bengio, Y. and Bottou, L. (eds.), Advances in Neural Information Processing Systems (NIPS), volume 21, pp. 1369-1376. Morgan Kaufmann Publishers.

    Rogers, S. and Girolami, M. (2005) A Bayesian regression approach to the inference of regulatory networks from gene expression data. Bioinformatics, 21, 3131-3137.

  • Related Research Results (1)
  • Metrics
    No metrics available
Share - Bookmark