Hierarchical semantic composition of biosimulation models using bond graphs.

Show simple item record

dc.contributor.author Shahidi, Niloofar
dc.contributor.author Pan, Michael
dc.contributor.author Safaei, Soroush
dc.contributor.author Tran, Kenneth
dc.contributor.author Crampin, Edmund J
dc.contributor.author Nickerson, David P
dc.coverage.spatial United States
dc.date.accessioned 2022-06-19T23:19:47Z
dc.date.available 2022-06-19T23:19:47Z
dc.date.issued 2021-05-13
dc.identifier.citation (2021). PLoS Computational Biology, 17(5), e1008859-.
dc.identifier.issn 1553-734X
dc.identifier.uri https://hdl.handle.net/2292/60000
dc.description.abstract Simulating complex biological and physiological systems and predicting their behaviours under different conditions remains challenging. Breaking systems into smaller and more manageable modules can address this challenge, assisting both model development and simulation. Nevertheless, existing computational models in biology and physiology are often not modular and therefore difficult to assemble into larger models. Even when this is possible, the resulting model may not be useful due to inconsistencies either with the laws of physics or the physiological behaviour of the system. Here, we propose a general methodology for composing models, combining the energy-based bond graph approach with semantics-based annotations. This approach improves model composition and ensures that a composite model is physically plausible. As an example, we demonstrate this approach to automated model composition using a model of human arterial circulation. The major benefit is that modellers can spend more time on understanding the behaviour of complex biological and physiological systems and less time wrangling with model composition.
dc.format.medium Electronic-eCollection
dc.language eng
dc.publisher Public Library of Science (PLoS)
dc.relation.ispartofseries PLoS computational biology
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher.
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject Arteries
dc.subject Humans
dc.subject Computational Biology
dc.subject Blood Circulation
dc.subject Models, Biological
dc.subject Models, Cardiovascular
dc.subject Semantics
dc.subject Computer Graphics
dc.subject Computer Simulation
dc.subject Software
dc.subject Networking and Information Technology R&D
dc.subject Science & Technology
dc.subject Life Sciences & Biomedicine
dc.subject Biochemical Research Methods
dc.subject Mathematical & Computational Biology
dc.subject Biochemistry & Molecular Biology
dc.subject BLOOD-FLOW
dc.subject MULTISCALE
dc.subject NETWORK
dc.subject CIRCULATION
dc.subject 01 Mathematical Sciences
dc.subject 06 Biological Sciences
dc.subject 08 Information and Computing Sciences
dc.title Hierarchical semantic composition of biosimulation models using bond graphs.
dc.type Journal Article
dc.identifier.doi 10.1371/journal.pcbi.1008859
pubs.issue 5
pubs.begin-page e1008859
pubs.volume 17
dc.date.updated 2022-05-17T00:12:22Z
dc.rights.holder Copyright: The author en
dc.identifier.pmid 33983945 (pubmed)
pubs.author-url https://www.ncbi.nlm.nih.gov/pubmed/33983945
pubs.publication-status Published
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Research Support, Non-U.S. Gov't
pubs.subtype research-article
pubs.subtype Journal Article
pubs.subtype Research Support, N.I.H., Extramural
pubs.elements-id 852842
pubs.org-id Bioengineering Institute
pubs.org-id ABI Associates
dc.identifier.eissn 1553-7358
dc.identifier.pii PCOMPBIOL-D-21-00472
pubs.number ARTN e1008859
pubs.record-created-at-source-date 2022-05-17
pubs.online-publication-date 2021-05-13

Files in this item

Find Full text

This item appears in the following Collection(s)

Show simple item record


Search ResearchSpace