Curve and surface fitting with splines
Curve and surface fitting with splines
Linear Modeling of Genetic Networks from Experimental Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
DS '02 Proceedings of the 5th International Conference on Discovery Science
CSB '02 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Learning the structure of dynamic probabilistic networks
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Inference, Modeling and Simulation of Gene Networks
CMSB '03 Proceedings of the First International Workshop on Computational Methods in Systems Biology
Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Learning dynamic Bayesian network models via cross-validation
Pattern Recognition Letters
International Journal of Data Mining and Bioinformatics
Generating probabilistic Boolean networks from a prescribed stationary distribution
Information Sciences: an International Journal
Analyzing the effect of prior knowledge in genetic regulatory network inference
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
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We propose a dynamic Bayesian network and nonparametric regression model for constructing a gene network from time series microarray gene expression data. The proposed method can overcome a shortcoming of the Bayesian network model in the sense of the construction of cyclic regulations. The proposed method can analyze the microarray data as continuous data and can capture even nonlinear relations among genes. It can be expected that this model will give a deeper insight into the complicated biological systems. We also derive a new criterion for evaluating an estimated network from Bayes approach. We demonstrate the effectiveness of our method by analyzing Saccharomyces cerevisiae gene expression data.