Semantic Reasoning and Knowledge Discovery in Biomedical Informatics Using Domain-Specific Ontologies

The introduction of domain-specific ontologies is revolutionizing the rapidly developing area of Biomedical Informatics by improving semantic reasoning and knowledge discovery. Using these ontologies, a complete framework for the extraction, organization, and analysis of complicated biological data is presented in this research. The framework provides deeper insights into biomedical research and healthcare practices by interpreting and connecting enormous arrays of heterogeneous data via the use of web technologies and sophisticated data mining methods. Accurate interpretation of biological concepts and their connections is made possible by semantic reasoning, which is supported by the structured representation of domain-specific ontologies. This leads to improved query performance, more precise data retrieval, and the development of complex inferential processes. The study also looks at how ontology-based data mining may be used to find new links and patterns, which might help with predictive modelling and the creation of hypotheses in biomedical research. The implementation obstacles are also discussed, such as scalability issues, data quality assurance, and ontology alignment and integration. The approach's major contributions to drug development, personalized medicine, and the larger field of biomedical research are highlighted in the paper's conclusion, which will eventually lead to better healthcare results and well-informed decisions.