The budding yeast cell cycle can be modeled by a set of ordinary differential
equations with 143 rate constant parameters. The quality of the model (and an associated vector of
parameter settings) is measured by comparing simulation results to the experimental data derived
from observing the cell cycles of over 100 selected mutated forms. Unfortunately, determining
whether the simulated phenotype matches experimental data is difficult since the experimental
data tend to be qualitative in nature (i.e., whether the mutation is viable, or which development
phase it died in). Because of this, previous methods for automatically comparing simulation results
to experimental data used a discontinuous penalty function, which limits the range of techniques
available for automated estimation of the differential equation parameters. This paper presents a
system of smooth inequality constraints that will be satisfied if and only if the model matches the
experimental data. Results are presented for evaluating the mutants with the two most frequent
phenotypes. This nonlinear inequality formulation is the first step toward solving a large-scale
feasibility problem to determine the ordinary differential equation model parameters