Compositional Techniques for Boolean Networks and Attractor Analysis

Recently a new compositional framework for constructing and analysing Boolean networks was presented based on merging entities using Boolean connectives. While this framework provides a good basis for engineering Boolean networks, its practical application is limited by the restricted composition structures allowed and the lack of support for attractor analysis. In this paper we significantly extend this compositional framework by developing a new general structure for compositions and by providing new techniques for compositionally identifying the attractors of a Boolean network. The results presented are important as they support ongoing work to use the framework for engineering biological systems and also provide a new basis for analysing Boolean networks which helps to address the practical limitations imposed by the state space explosion problem.