The development process is modeled as the development of gene expression states.  The gene expression pattern  at time  is defined as the initial expression state.  The interactions among genes change the expression states during the development process.  This process is modeled by the following differential equations
where τ) represents the expression state of  at time .  It is determined by a filter function σ.   represents the weighted sum of regulatory effects () of all genes on gene  at time .  In the original Wagner model, the filter function is a step function
In other variants, the filter function is implemented as a sigmoidal function
In this way, the expression states will acquire a continuous distribution. The gene expression will reach the final state if it reaches a stable pattern.