title: Ontology-based instance data validation for high-quality curated biological pathways.
abstract: BACKGROUND
  Modeling in systems biology is vital for understanding the complexity of biological systems across scales and predicting system-level behaviors. To obtain high-quality pathway databases, it is essential to improve the efficiency of model validation and model update based on appropriate feedback.
  
  
  RESULTS
  We have developed a new method to guide creating novel high-quality biological pathways, using a rule-based validation. Rules are defined to correct models against biological semantics and improve models for dynamic simulation. In this work, we have defined 40 rules which constrain event-specific participants and the related features and adding missing processes based on biological events. This approach is applied to data in Cell System Ontology which is a comprehensive ontology that represents complex biological pathways with dynamics and visualization. The experimental results show that the relatively simple rules can efficiently detect errors made during curation, such as misassignment and misuse of ontology concepts and terms in curated models.
  
  
  CONCLUSIONS
  A new rule-based approach has been developed to facilitate model validation and model complementation. Our rule-based validation embedding biological semantics enables us to provide high-quality curated biological pathways. This approach can serve as a preprocessing step for model integration, exchange and extraction data, and simulation.
authors.affiliation: Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan. eajeong@ims.u-tokyo.ac.jp
authors.forename: Euna
authors.initials: E
authors.lastname: Jeong
authors.forename: Masao
authors.initials: M
authors.lastname: Nagasaki
authors.forename: Kazuko
authors.initials: K
authors.lastname: Ueno
authors.forename: Satoru
authors.initials: S
authors.lastname: Miyano
mesh_terms: D003198:Computer Simulation; D008954:Models, Biological; D049490:Systems Biology / Q000379:methods*; D054928:Validation Studies as Topic