Local Structure and Behavior of Boolean Bioregulatory Networks

Abstract. A well-known discrete approach to modeling biological regulatory networks is the logical framework developed by R. Thomas. The network structure is captured in an interaction graph, which, together with a set of Boolean parameters, gives rise to a state transition graph describing the dynamical behavior. Together with E. H. Snoussi, Thomas later extended the framework by including singular values representing the threshold values of interactions. A systematic approach was taken in [10] to link circuits in the interaction graph with character and number of attractors in the state transition graph by using the information inherent in singular steady states. In this paper, we employ the concept of local interaction graphs to strengthen the results in [10]. Using the local interaction graph of a singular steady state, we are able to construct attractors of the regulatory network from attractors of certain subnetworks. As a comprehensive generalization of the framework introduced ...

• Type: Conference
• Year: 2008
• Where: AB
• Authors: Heike Siebert
• Keywords: AB 2008, Computational Biology, Interaction Graph, Singular Steady State, State Transition Graph