Modelling Gene Expression Data using Dynamic Bayesian Networks

@inproceedings{Murphy1999ModellingGE,
  title={Modelling Gene Expression Data using Dynamic Bayesian Networks},
  author={Kevin Murphy and Saira Mian},
  year={1999}
}
Recently, there has been much interest in reverse engineering genetic networks from time series data. In this paper, we show that most of the proposed discrete time models — including the boolean network model [Kau93, SS96], the linear model of D’haeseleer et al. [DWFS99], and the nonlinear model of Weaver et al. [WWS99] — are all special cases of a general class of models called Dynamic Bayesian Networks (DBNs). The advantages of DBNs include the ability to model stochasticity, to incorporate… CONTINUE READING
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