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This article describes computational problems that arise in representing knowledge about the metabolism in electronic form, in analyzing that knowledge to gain deeper insights into complexities of the metabolism, and in applying that knowledge to biology, biotechnology, and health care. These problems push the limits of existing techniques for knowledge representation, planning, integration of heterogeneous databases, qualitative reasoning, knowledge acquisition and machine learning. This article surveys several recent and ongoing efforts to solve these problems, including the EcoCyc project, a collaborative effort of the Marine Biological Laboratory, SRI International, and the National Library of Medicine.>
Karp et al. (Fri,) studied this question.