Abstract
A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of the model and is thus a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test since it requires to solve a system of algebraic nonlinear equations which increases in nonlinearity degree and number of terms and unknowns with model order. In this paper a computer algebra tool GLOBI (GLOBal Identifiability) to test global identifiability of linear companmental models is presented which combines the topological transfer function method With the Buchberger algoritlun. GLOBI allows to automatically test a priori global identifiability of general structure compartmental models from general multi input-multi output experiments
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