Optimal state estimation for boolean dynamical systems using a boolean Kalman smoother

This paper is concerned with state estimation at a fixed time point in a given time series of observations of a Boolean dynamical system. Towards this end, we introduce the Boolean Kalman Smoother, which provides an efficient algorithm to compute the optimal MMSE state estimator for this problem. Performance is investigated using a Boolean network model of the p53-MDM2 negative feedback loop gene regulatory network observed through time series of Next-Generation Sequencing (NGS) data.