In this paper, as a model of the genetic networks, we propose the probabilistic boolean network model as the intermediate model. And then we give an efficient method to identify the probabilistic boolean network from data. As the model selection criteria, we employ the minimum desctiption length (MDL) principle. Given fixed $k$ input variable, finding maximum likelihood probabilistic boolean concept takes $O(2^{2^k})$ by the naive solution. However, based on the computational geometric algorithm that finds region which minimizes a convex objective function introduced by Morimoto et.al. \cite{Morimoto98}, we can find the (nearly) optimal model efficiently.
By: Hisashi Kashima
Published in: RT0392 in 2002
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