Date(s) - 25/03/2019
15 h 00 min - 16 h 00 min
Catégories Pas de Catégories
Logical models of gene regulatory networks are essential to understand cellular processes. However, the definition of such models is mostly still manually performed, and consequently prone to error. Also, as new experimental data is acquired, these models often need to be revised and updated.
We propose a model revision tool, based on Answer Set Programming, capable of proposing the set of minimum repairs to render a model consistent with a set of experimental observations. We consider four possible repair operations, giving preference to repairs on regulatory functions over topological ones. Also, we consider observations at stable state, i.e, we do not consider the model dynamics.
We evaluate our tool on five known logical models. We perform random changes considering several parameter configurations to assess the tool repairing capabilities. Whenever a model is repaired under the time limit, the tool successfully produces the optimal solutions to repair the model. Also, the number of repair operations required is less than or equal to the number of random changes applied to the original model.