Ontological Reasoning for Understanding the Behaviour of Complex Biomolecular Networks

Analysis of biological systems is being progressively facilitated by computational tools. Most of these tools are based on qualitative and numerical methods. However, they are not always evident and there is an increasing need to provide an additional semantic layer. Semantic technologies, especially ontologies, are one of the tools frequently used for this purpose. In fact, they are indispensable for understanding the semantic knowledge about the functioning of cells on a molecular level. We describe here the biomolecular network ontology (BNO) created specially to address the needs of analysing the complex biomolecular network's behaviour. The BNO ontology is freely available at https://github.com/AliAyadi/The-BiomolecularNetwork-Ontology and can be viewed using the standard ontology visualization editor Protégé. This ontology provides qualitative simulation of large and complex biomolecular networks. Therefore, in order to evaluate the efficacy of the BNO ontology we present two kinds of reasoning mechanisms. The first consists on an SWRL rule based reasoning developed using the SWRL rules editor tab, and another consists on an implementation of a rule-based system under the MATLAB/SIMULINK development environment and can be freely downloaded at https://github.com/AliAyadi/QualitativeReasoningInMATLAB. Both of these reasoning mechanisms have been applied to the analysis of a real network of biological interest, the "bacteriophage T4 gene 32" use case.