A semantics, energy-based approach to automate biomodel composition.
Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address th...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0269497&type=printable |
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| author | Niloofar Shahidi Michael Pan Kenneth Tran Edmund J Crampin David P Nickerson |
| author_facet | Niloofar Shahidi Michael Pan Kenneth Tran Edmund J Crampin David P Nickerson |
| author_sort | Niloofar Shahidi |
| collection | DOAJ |
| description | Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address these challenges in integrating biosimulation models, we propose an approach to automatically and confidently compose biosimulation models. The approach uses bond graphs to combine aspects of physical and thermodynamics-based modelling with biological semantics. We improved on existing approaches by using semantic annotations to automate the recognition of common components. The approach is illustrated by coupling a model of the Ras-MAPK cascade to a model of the upstream activation of EGFR. Through this methodology, we aim to assist researchers and modellers in readily having access to more comprehensive biological systems models. |
| format | Article |
| id | doaj-art-49da626ad8ac4dbbaf8e0ed34b5fc29c |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-49da626ad8ac4dbbaf8e0ed34b5fc29c2025-08-20T03:01:59ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01176e026949710.1371/journal.pone.0269497A semantics, energy-based approach to automate biomodel composition.Niloofar ShahidiMichael PanKenneth TranEdmund J CrampinDavid P NickersonHierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address these challenges in integrating biosimulation models, we propose an approach to automatically and confidently compose biosimulation models. The approach uses bond graphs to combine aspects of physical and thermodynamics-based modelling with biological semantics. We improved on existing approaches by using semantic annotations to automate the recognition of common components. The approach is illustrated by coupling a model of the Ras-MAPK cascade to a model of the upstream activation of EGFR. Through this methodology, we aim to assist researchers and modellers in readily having access to more comprehensive biological systems models.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0269497&type=printable |
| spellingShingle | Niloofar Shahidi Michael Pan Kenneth Tran Edmund J Crampin David P Nickerson A semantics, energy-based approach to automate biomodel composition. PLoS ONE |
| title | A semantics, energy-based approach to automate biomodel composition. |
| title_full | A semantics, energy-based approach to automate biomodel composition. |
| title_fullStr | A semantics, energy-based approach to automate biomodel composition. |
| title_full_unstemmed | A semantics, energy-based approach to automate biomodel composition. |
| title_short | A semantics, energy-based approach to automate biomodel composition. |
| title_sort | semantics energy based approach to automate biomodel composition |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0269497&type=printable |
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