Abstract:We
address the system identification problem of genetic networks
using noisy and correlated time series data of gene expression level
measurements. Least-squares (LS) is a commonly used method for the
parameter estimation in the network reconstruction problems. The LS
algorithm implicitly assumes that the measurement noise is confined
only to the dependent variables. However, a discrete time model for
the genetic network systems will lead to serially correlated noise
terms that appear in both the dependent and… Show more
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