Fig_1.tif (508.95 kB)

Model construction and optimization workflow.

Download (0 kB)
posted on 05.08.2015 by Anastasia Chasapi, Paulina Wachowicz, Anne Niknejad, Philippe Collin, Andrea Krapp, Elena Cano, Viesturs Simanis, Ioannis Xenarios

The Prior Knowledge Network (PKN) is constructed after collecting relevant information from various sources, including network databases and literature. The PKN is translated into logical functions, describing the regulatory relations among gene products. The logical model is simulated under the preferred conditions, resulting in one or more steady states, where all logical rules are satisfied. The model goes then through an optimization procedure, where the goal is to fit the resulting steady states with available experimental data by altering regulatory rules. The optimization typically includes removing outdated / low confidence links, adjusting their representation and adding new regulatory rules. The process is iterated until the simulation fits the available data. The model can then be used as a predictive tool, by performing in silico perturbations. Validation of the predictions can lead to discovery of missing regulatory links that are then added to the PKN.