BNO - An Ontology for Understanding the Transittability of Complex Biomolecular Networks

Abstract

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. Indeed, they are indispensable for understanding the semantic knowledge about the operation of cells at 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. A biomolecular network consists of nodes, denoting cellular entities, and edges, representing interactions among cellular components. The BNO ontology provides a foundation for qualitative simulation of complex biomolecular networks. We test the performance of the proposed BNO ontology by using a real example of a biomolecular network, the bacteriophage T4 gene 32. We illustrate the proposed BNO ontology for reasoning and inferring new knowledge with sets of rules expressed in SWRL. Results demonstrate that the BNO ontology allows to precisely interpret the corresponding semantic context and intelligently model biomolecular networks and their state changes. The Biomolecular Network Ontology (BNO) is freely available at https://github.com/AliAyadi/BNO-ontology-version-1.0.

Keywords: systems biology, complex biomolecular networks, transittability, ontology engineering, qualitative reasoning, SWRL rules