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We consider a specific class of polynomial systems that arise in parameteridentifiability problems of models of ordinary differential equations (ODE) anddiscover a method for speeding up the Gr\"obner basis computation by usingspecific variable ordering and weights coming from the structure of the ODEmodel. We provide empirical results that show improvement across differentsymbolic computing frameworks.

Faster Gr\"obner Bases via Domain-Specific Ordering in Parameter Identifiability of ODE Models