Artiﬁcial neural networks, electronic circuits, and gene networks are some examples of systems that can be modeled as networks, that is, as collections of interconnected nodes. In this paper we introduce the concept of terminal graph (t-graph for short), which improves on the concept of graph as a unifying principle for the representation and computational synthesis and inference of technological and biological networks. We begin by showing how to use the t-graph concept to better understand the working of existing methods for the computational synthesis of networks. Then, we discuss the issue of the “missing methods”, that is, of new computational methods of network synthesis whose existence can be inferred using the perspective provided by the con- cept of t-graph. Finally, we comment on the application of the t-graph perspective to problems of network inference, to the ﬁeld of complex networks, social networks, and to the understanding of biological networks and developmental processes.