Ontology-based instance data validation for high-quality curated biological pathways
<p>Abstract</p> <p>Background</p> <p>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 m...
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doaj-6914069032d749cf92cc30c903f3e5c92020-11-25T00:35:10ZengBMCBMC Bioinformatics1471-21052011-02-0112Suppl 1S810.1186/1471-2105-12-S1-S8Ontology-based instance data validation for high-quality curated biological pathwaysUeno KazukoNagasaki MasaoJeong EunaMiyano Satoru<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p> |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ueno Kazuko Nagasaki Masao Jeong Euna Miyano Satoru |
spellingShingle |
Ueno Kazuko Nagasaki Masao Jeong Euna Miyano Satoru Ontology-based instance data validation for high-quality curated biological pathways BMC Bioinformatics |
author_facet |
Ueno Kazuko Nagasaki Masao Jeong Euna Miyano Satoru |
author_sort |
Ueno Kazuko |
title |
Ontology-based instance data validation for high-quality curated biological pathways |
title_short |
Ontology-based instance data validation for high-quality curated biological pathways |
title_full |
Ontology-based instance data validation for high-quality curated biological pathways |
title_fullStr |
Ontology-based instance data validation for high-quality curated biological pathways |
title_full_unstemmed |
Ontology-based instance data validation for high-quality curated biological pathways |
title_sort |
ontology-based instance data validation for high-quality curated biological pathways |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2011-02-01 |
description |
<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p> |
work_keys_str_mv |
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1725309919530319872 |