Protein ontology on the semantic web for knowledge discovery

Area of Science:

• Proteomics
• Bioinformatics
• Semantic Web Technologies

Background:

• The Protein Ontology (PRO) organizes protein-related entities, including families, proteoforms, and complexes.
• Integrating biological data is crucial for advancing knowledge discovery.

Purpose of the Study:

• To expose, share, and connect protein knowledge on the Semantic Web using RDF.
• To enable biological knowledge discovery by integrating PRO data with other Linked Open Data.

Main Methods:

• Utilizing Resource Description Framework (RDF) for data representation.
• Implementing a faceted browser interface and SPARQL endpoint for data exploration.
• Providing RESTful APIs for programmatic data access and downloadable RDF data dumps.

Main Results:

• PRO Linked Open Data (LOD) facilitates the retrieval of proteins and variants based on disease associations.
• The resource adheres to Findability, Accessibility, Interoperability, and Reusability (FAIR) principles.
• Multiple data access and querying methods are supported for diverse user needs.

Conclusions:

• PRO LOD enhances biological knowledge discovery through linked data principles.
• The resource provides accessible and interoperable protein information for scientists and programmers.
• Adherence to FAIR principles ensures the long-term value and usability of the PRO LOD resource.