TGG Based Automatic Transformation Between SBML and Other Biological Modeling Languages

XSLT based transformation, between SBML and other biological modeling languages, cannot describe comprehensive context-sensitive semantic correspondences among the inner elements of biological modeling objects; cannot guarantee the determinacy and syntactic correctness of transformation results; and also cannot meet industrial transformation requirements. Toward these problems, a triple graph grammar (TGG) based transformation method is presented, which utilizes graph grammars to define SBML schema and other biological modeling languages, and utilizes TGG to construct transformation between them. On this basis, a transformation algorithm is presented, which has polynomial time complexity and can guarantee determinacy and syntactic correctness. Compared with the traditional transformation between SBML and other biological modeling languages, the method in this paper has the following characteristics: 1) It utilizes context-sensitive grammar and has strong description capability; 2) It imposes graph-based approach to simplify transformation definition process; 3) It only needs static analysis of transformation rules at the design time without exploring dynamic analysis, because validation must be achieved if transformation rules satisfy some constraints; 4) It only requires to change direction of transformation rules to implement bi-directional transformation, without modifying any element; and 5) It supports incremental change propagation, since it preserves the correspondence information between source and target objects. Finally, correctness and effectiveness of this method are verified through an example of transformation between Petri net and SBML.