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Linear compartmental models are useful, explanatory tools, that have been widely used to represent the dynamic behavior of complex biological systems. This paper addresses the problem of the numerical identification of such models, i.e., the estimation of the parameter values that will generate predictions closest to experimental observations. Traditional local optimization techniques find it difficult...
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