Evolutionary Design of Synthetic Gene Networks by Means of a Semantic Expert System

In the last decade many researchers proposed tools and methods for the automatic generation of synthetic biological devices with desired functions. However, advances in synthetic biology have been limited by a lack of frameworks meeting the essential requirements of standardization, modularity, complexity and re-use. The present work tries to cope with the standardization issue by the adoption of model exchange standards like CellML, BioBrick standard biological parts and standard signal carriers for modeling purpose. The generated models are made of SVP modular components. Model complexity includes more interaction dynamics than previous works. The inherent software complexity has been handled by a rational use of ontologies and rule engine. The database of parts and interactions is automatically created from publicly available whole system models. Built on this automatic modeling component, a genetic algorithm has been implemented, that searches the space of possible genetic circuits for an optimal circuit meeting user defined input-output dynamics. The system has been successfully tested on two test cases. This work proposes a new approach able of pushing forward the complexity managed by genetic circuits automatic design tools.