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Representing physiological processes and their participants with PhysioMaps
BACKGROUND: As the number and size of biological knowledge resources for physiology grows, researchers need improved tools for searching and integrating knowledge and physiological models. Unfortunately, current resources—databases, simulation models, and knowledge bases, for example—are only occasi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3632997/ https://www.ncbi.nlm.nih.gov/pubmed/23735231 http://dx.doi.org/10.1186/2041-1480-4-S1-S2 |
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author | Cook, Daniel L Neal, Maxwell L Hoehndorf, Robert Gkoutos, Georgios V Gennari, John H |
author_facet | Cook, Daniel L Neal, Maxwell L Hoehndorf, Robert Gkoutos, Georgios V Gennari, John H |
author_sort | Cook, Daniel L |
collection | PubMed |
description | BACKGROUND: As the number and size of biological knowledge resources for physiology grows, researchers need improved tools for searching and integrating knowledge and physiological models. Unfortunately, current resources—databases, simulation models, and knowledge bases, for example—are only occasionally and idiosyncratically explicit about the semantics of the biological entities and processes that they describe. RESULTS: We present a formal approach, based on the semantics of biophysics as represented in the Ontology of Physics for Biology, that divides physiological knowledge into three partitions: structural knowledge, process knowledge and biophysical knowledge. We then computationally integrate these partitions across multiple structural and biophysical domains as computable ontologies by which such knowledge can be archived, reused, and displayed. Our key result is the semi-automatic parsing of biosimulation model code into PhysioMaps that can be displayed and interrogated for qualitative responses to hypothetical perturbations. CONCLUSIONS: Strong, explicit semantics of biophysics can provide a formal, computational basis for integrating physiological knowledge in a manner that supports visualization of the physiological content of biosimulation models across spatial scales and biophysical domains. |
format | Online Article Text |
id | pubmed-3632997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36329972013-04-25 Representing physiological processes and their participants with PhysioMaps Cook, Daniel L Neal, Maxwell L Hoehndorf, Robert Gkoutos, Georgios V Gennari, John H J Biomed Semantics Proceedings BACKGROUND: As the number and size of biological knowledge resources for physiology grows, researchers need improved tools for searching and integrating knowledge and physiological models. Unfortunately, current resources—databases, simulation models, and knowledge bases, for example—are only occasionally and idiosyncratically explicit about the semantics of the biological entities and processes that they describe. RESULTS: We present a formal approach, based on the semantics of biophysics as represented in the Ontology of Physics for Biology, that divides physiological knowledge into three partitions: structural knowledge, process knowledge and biophysical knowledge. We then computationally integrate these partitions across multiple structural and biophysical domains as computable ontologies by which such knowledge can be archived, reused, and displayed. Our key result is the semi-automatic parsing of biosimulation model code into PhysioMaps that can be displayed and interrogated for qualitative responses to hypothetical perturbations. CONCLUSIONS: Strong, explicit semantics of biophysics can provide a formal, computational basis for integrating physiological knowledge in a manner that supports visualization of the physiological content of biosimulation models across spatial scales and biophysical domains. BioMed Central 2013-04-15 /pmc/articles/PMC3632997/ /pubmed/23735231 http://dx.doi.org/10.1186/2041-1480-4-S1-S2 Text en Copyright © 2013 Cook et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Cook, Daniel L Neal, Maxwell L Hoehndorf, Robert Gkoutos, Georgios V Gennari, John H Representing physiological processes and their participants with PhysioMaps |
title | Representing physiological processes and their participants with PhysioMaps |
title_full | Representing physiological processes and their participants with PhysioMaps |
title_fullStr | Representing physiological processes and their participants with PhysioMaps |
title_full_unstemmed | Representing physiological processes and their participants with PhysioMaps |
title_short | Representing physiological processes and their participants with PhysioMaps |
title_sort | representing physiological processes and their participants with physiomaps |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3632997/ https://www.ncbi.nlm.nih.gov/pubmed/23735231 http://dx.doi.org/10.1186/2041-1480-4-S1-S2 |
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