In this paper we consider networks of evolutionary processors with splicing rules (NEPS) as language generating and computational devices. Such a network consists of several processors placed on the nodes of a virtual graph and are able to perform splicing (which is a biologically motivated operation) on the words present in that node, according to the splicing rules present there. Each node is associated with an input and output filter. When the filters are regular languages one gets the computational power of Turing machines with networks of size two. We also show how these networks can be used to solve NP-complete problems in linear time. © Springer-Verlag Berlin Heidelberg 2005.