Logical Gene Ontology Annotations (GOAL): exploring gene ontology annotations with OWL

Area of Science:

• Bioinformatics
• Ontology Engineering
• Computational Biology

Background:

• Gene Ontology (GO) and Open Biomedical Ontologies (OBO) facilitate cross-species gene comparisons and analysis.
• Current tools lack multi-perspective querying across different ontologies for gene products.
• Automated reasoning on ontology semantics can enhance gene product annotation querying.

Purpose of the Study:

• To develop a multi-perspective, richer querying system for gene product annotations.
• To integrate the Gene Ontology, Human Disease Ontology, and Mammalian Phenotype Ontology.
• To enable complex queries linking gene function, phenotype, and disease.

Main Methods:

• Created the Logical Gene Ontology (GOAL) in OWL, combining GO, Human Disease Ontology, and Mammalian Phenotype Ontology.
• Represented mouse gene products as classes with relationships to GO aspects, phenotype, and disease annotations.
• Utilized defined classes and automated reasoning for querying and building gene product hierarchies.
• Developed a web interface for constructing arbitrary queries and displaying results.

Main Results:

• The GOAL ontology provides a rich interaction with multiple ontology annotations for mouse gene products.
• Automated reasoning enables effective cross-ontology querying for biologically relevant questions.
• A complex hierarchy of mouse gene products was constructed based on integrated annotations.
• A web interface was developed for user-friendly, arbitrary querying of the GOAL ontology.

Conclusions:

• OWL and automated reasoning effectively query across ontologies for biologically rich questions.
• The GOAL ontology allows fine partitioning of mouse gene products through integrated annotations.
• Automated reasoning provides practical online querying support for mouse ontology annotations.
• The GOAL system facilitates advanced analysis of gene product information.