Title: In silico evolution of signaling networks using rule-based models: bistable response dynamics,
Abstract: One of the ultimate goals in biology is to understand the design principles
of biological systems. Such principles, if they exist, can help us better
understand complex, natural biological systems and guide the engineering of de
novo ones. Towards deciphering design principles, in silico evolution of
biological systems with proper abstraction is a promising approach. Here, we
demonstrate the application of in silico evolution combined with rule-based
modelling for exploring design principles of cellular signaling networks. This
application is based on a computational platform, called BioJazz, which allows
in silico evolution of signaling networks with unbounded complexity. We provide
a detailed introduction to BioJazz architecture and implementation and describe
how it can be used to evolve and/or design signaling networks with defined
dynamics. For the latter, we evolve signaling networks with switch-like
response dynamics and demonstrate how BioJazz can result in new biological
insights on network structures that can endow bistable response dynamics. This
example also demonstrated both the power of BioJazz in evolving and designing
signaling networks and its limitations at the current stage of development.