Knowledge representation model for systems-level analysis of signal transduction networks

A Petri-net based model for knowledge representation has been developed to describe as explicitly and formally as possible the molecular mechanisms of cell signaling and their pathological implications. A conceptual framework has been established for reconstructing and analyzing signal transduction networks on the basis of the formal representation. Such a conceptual framework renders it possible to qualitatively understand the cell signaling behavior at systems-level. The mechanisms of the complex signaling network are explored by applying the established framework to the signal transduction induced by potent proinflammatory cytokines, IL-1beta and TNF-alpha The corresponding expert-knowledge network is constructed to evaluate its mechanisms in detail. This strategy should be useful in drug target discovery and its validation.