State-space approach with the maximum likelihood principle to identify the system generating time-course gene expression data of yeast
نویسندگان
چکیده
We use linear Gaussian state-space models to analyse time-course gene expression data of yeast. They are modelled to be generated from hidden state variables in a system. To identify the system, we estimate parameters of the model by EM algorithm and determine the dimension of the state variable by BIC.
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عنوان ژورنال:
- International journal of data mining and bioinformatics
دوره 1 1 شماره
صفحات -
تاریخ انتشار 2006