Abstract: A network association mining algorithm and associated methods are presented which accepts data from biological and other experiments and automatically produces a network and attempts to explain the behavior of the biological or other system underlying the data using evolutionary techniques. The model and associated methods aim to identify the inter-relationships consistent with data and other prior knowledge supplied to the system. The network is represented in terms of coupled dynamical system. These dynamical systems are represented by differential or difference equations to educe these dynamical systems and coupling between them, an evolutionary algorithm is used. The output of the linkage finder could assist scientists to better understand the systems underlying and to guess at surrogate data.