We have developed a knowledge-based but partially analytic simulation system. This system simulates regulatory action in lambda phage, a virus which infects E. coli. Specifically, we simulated the decision between its two developmental pathways, lytic and lysogenic growth. Our model is composed of two levels: roughly abstracted level and precisely abstracted level. The former level is discrete-event and knowledge-based. It covers overall regulations inside lambda phage in qualitative representation. On the other hand, the latter is based on quantitative chemical equations describing the sensitive bifurcation within pathways. In this way, qualitatively clear overview of regulatory action is efficiently simulated using knowledge base, and only the unpredictable part is analytically simulated in detail. This system can output not only input knowledge but also precise prediction by computational analysis, data which help molecular biologists find new theories of regulatory actions.
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