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RIMBO - An Ontology for Model Revision Databases
Chalmers University of Technology, Gothenburg, Sweden.ORCID iD: 0000-0002-3011-5541
Chalmers University of Technology, Gothenburg, Sweden.ORCID iD: 0000-0002-8358-0842
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology. Chalmers University of Technology, Gothenburg, Sweden.ORCID iD: 0000-0002-0408-3515
Chalmers University of Technology, Gothenburg, Sweden; University of Cambridge, Cambridge, UK; Alan Turing Institute, London, UK.ORCID iD: 0000-0001-7208-4387
2023 (English)In: Discovery Science - 26th International Conference, DS 2023, Proceedings, Springer Nature , 2023, p. 523-534Conference paper, Published paper (Refereed)
Abstract [en]

The use of computational models is growing throughout most scientific domains. The increased complexity of such models, as well as the increased automation of scientific research, imply that model revisions need to be systematically recorded. We present RIMBO (Revisions for Improvements of Models in Biology Ontology), which describes the changes made to computational biology models. The ontology is intended as the foundation of a database containing and describing iterative improvements to models. By recording high level information, such as modelled phenomena, and model type, using controlled vocabularies from widely used ontologies, the same database can be used for different model types. The database aims to describe the evolution of models by recording chains of changes to them. To make this evolution transparent, emphasise has been put on recording the reasons, and descriptions, of the changes. We demonstrate the usefulness of a database based on this ontology by modelling the update from version 8.4.1 to 8.4.2 of the genome-scale metabolic model Yeast8, a modification proposed by an abduction algorithm, as well as thousands of simulated revisions. This results in a database demonstrating that revisions can successfully be modelled in a semantically meaningful and storage efficient way. We believe such a database is necessary for performing automated model improvement at scale in systems biology, as well as being a useful tool to increase the openness and traceability for model development. With minor modifications the ontology can also be used in other scientific domains. The ontology is made available at https://github.com/filipkro/rimbo and will be continually updated.

Place, publisher, year, edition, pages
Springer Nature , 2023. p. 523-534
Keywords [en]
Computational biology, Database, Knowledge representation, Ontology, Semantic web
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:kth:diva-349999DOI: 10.1007/978-3-031-45275-8_35ISI: 001455440700035Scopus ID: 2-s2.0-85174297834OAI: oai:DiVA.org:kth-349999DiVA, id: diva2:1882420
Conference
26th International Conference on Discovery Science, DS 2023, Porto, Portugal, Oct 9 2023 - Oct 11 2023
Note

Part of ISBN 9783031452741

QC 20240705

Available from: 2024-07-05 Created: 2024-07-05 Last updated: 2025-12-08Bibliographically approved

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Tiukova, Ievgeniia A.

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