In silico simulation of signal cascades in biomedical networks based on the production rule system

Abstract

Inferring novel findings from known biological knowledge is one of the ultimate goals in systems biology. However, the observation of system-level responses to a given perturbation has not been thoroughly explored due to the lack of proper large-scale inference models. We developed a novel expert system that can be applied to conventional biological networks based on the production rule system which works by transforming networks into a knowl-edgebase. Testing on large-scale multi-level biomedical networks confirmed the applicability of our system and revealed that hundreds of molecules are affected by the cascades of given signals, thereby activating or repressing key pathways in a cell.