Ontologies in bioinformatics and systems biology

Abstract

Computer simulation is now becoming a central scientific paradigm of systems biology and a basic tool for the theoretical study and understanding of the complex mechanisms of living systems. The increase in the number and complexity of these models leads to the need for their collaborative development, reuse of models, their verification, and the description of computational experiments and their results. Ontological modeling is used to develop formats for knowledge-oriented mathematical modeling of biological systems. In this sense, ontology associated with the entire set of formats that support research in systems biology, in particular, computer modeling of biological systems and processes, can be regarded as a first approximation to the ontology of systems biology. This review summarizes the features of the subject area (bioinformatics, systems biology, and biomedicine), the main motivation for the development of ontologies and the most important examples of ontological modeling and semantic analysis at different levels of the hierarchy of knowledge: molecular genetic, cellular, tissue, organs, and the body. Bioinformatics and systems biology is an excellent ground for testing the technologies and efficient use of ontological modeling. Several dozens of verified basic reference ontologies now represent a source of knowledge for the integration and development of more complex domain models aimed at addressing specific issues in biomedicine and biotechnology. Further formalization and ontological accumulation of knowledge and the use of formal methods of analysis can take the entire cycle of research in systems biology to a new technological level.