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Updated: Jul 6, 2026

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Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response
Published on: August 10, 2017
State-space approach with the maximum likelihood principle to identify the system generating time-course gene
Rui Yamaguchi1, Tomoyuki Higuchi
1Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan. ruiy@ims.u-tokyo.ac.jp
International Journal of Data Mining and Bioinformatics
|April 12, 2008
Abstract:
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.

