  Rule-based modeling is a powerful way to model kinetic interactions in
biochemical systems. Rules enable a precise encoding of biochemical
interactions at the resolution of sites within molecules, but obtaining an
integrated global view from sets of rules remains challenging. Current
automated approaches to rule visualization fail to address the complexity of
interactions between rules, limiting either the types of rules that are allowed
or the set of interactions that can be visualized simultaneously. There is a
need for scalable visualization approaches that present the information encoded
in rules in an intuitive and useful manner at different levels of detail. We
have developed new automated approaches for visualizing both individual rules
and complete rule-based models. We find that a more compact representation of
an individual rule promotes promotes understanding the model assumptions
underlying each rule. For global visualization of rule interactions, we have
developed a method to synthesize a network of interactions between sites and
processes from a rule-based model and then use a combination of user-defined
and automated approaches to compress this network into a readable form. The
resulting diagrams enable modelers to identify signaling motifs such as
cascades, feedback loops, and feed-forward loops in complex models, as we
demonstrate using several large-scale models. These capabilities are
implemented within the BioNetGen framework but the approach is equally
applicable to rule-based models specified in other formats.
