ARTIFICIAL INTELLIGENCE FOR ANALYZING HYPOTHETICAL MODELS

摘要

Biology models of biochemical systems have proven to be powerful conceptual tools for the analysis of biological data. Biological data is unique in that it exists mostly in the differential display format. The present invention (Fig. 1) uses artificial intelligence (AI) to synthesize bioinformatic data (unit operations) for building and analyzing models of underlying physiologies (hypothetical mathematical models). In addition to AI methods, the invention describes the use of differential equations [e.g. the Michaelis-Menton kinetics equation, d/dt(Substrate[t])=-Enzyme[t]Substrate[t]/(Km+Substrate[t])] and linear algebra (i.e. the linear differential equation of the Michaelis-Menton kinetics equation and its Laplace transform) to recast the models into another mathematical domain. The direct use of differential display data formats for model testing provides more complete alternatives for modeling physiological and other complex systems towards a global solution.