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Multiscale Modeling and Data Integration in the Virtual Physiological Rat Project
It has become increasingly evident that the descriptions of many complex diseases are only possible by taking into account multiple influences at different physiological scales. To do this with computational models often requires the integration of several models that have overlapping scales (genes...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463790/ https://www.ncbi.nlm.nih.gov/pubmed/22805979 http://dx.doi.org/10.1007/s10439-012-0611-7 |
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author | Beard, Daniel A. Neal, Maxwell L. Tabesh-Saleki, Nazanin Thompson, Christopher T. Bassingtwaighte, James B. Shimoyama, Mary Carlson, Brian E. |
author_facet | Beard, Daniel A. Neal, Maxwell L. Tabesh-Saleki, Nazanin Thompson, Christopher T. Bassingtwaighte, James B. Shimoyama, Mary Carlson, Brian E. |
author_sort | Beard, Daniel A. |
collection | PubMed |
description | It has become increasingly evident that the descriptions of many complex diseases are only possible by taking into account multiple influences at different physiological scales. To do this with computational models often requires the integration of several models that have overlapping scales (genes to molecules, molecules to cells, cells to tissues). The Virtual Physiological Rat (VPR) Project, a National Institute of General Medical Sciences (NIGMS) funded National Center of Systems Biology, is tasked with mechanistically describing several complex diseases and is therefore identifying methods to facilitate the process of model integration across physiological scales. In addition, the VPR has a considerable experimental component and the resultant data must be integrated into these composite multiscale models and made available to the research community. A perspective of the current state of the art in model integration and sharing along with archiving of experimental data will be presented here in the context of multiscale physiological models. It was found that current ontological, model and data repository resources and integrative software tools are sufficient to create composite models from separate existing models and the example composite model developed here exhibits emergent behavior not predicted by the separate models. |
format | Online Article Text |
id | pubmed-3463790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-34637902012-10-04 Multiscale Modeling and Data Integration in the Virtual Physiological Rat Project Beard, Daniel A. Neal, Maxwell L. Tabesh-Saleki, Nazanin Thompson, Christopher T. Bassingtwaighte, James B. Shimoyama, Mary Carlson, Brian E. Ann Biomed Eng Article It has become increasingly evident that the descriptions of many complex diseases are only possible by taking into account multiple influences at different physiological scales. To do this with computational models often requires the integration of several models that have overlapping scales (genes to molecules, molecules to cells, cells to tissues). The Virtual Physiological Rat (VPR) Project, a National Institute of General Medical Sciences (NIGMS) funded National Center of Systems Biology, is tasked with mechanistically describing several complex diseases and is therefore identifying methods to facilitate the process of model integration across physiological scales. In addition, the VPR has a considerable experimental component and the resultant data must be integrated into these composite multiscale models and made available to the research community. A perspective of the current state of the art in model integration and sharing along with archiving of experimental data will be presented here in the context of multiscale physiological models. It was found that current ontological, model and data repository resources and integrative software tools are sufficient to create composite models from separate existing models and the example composite model developed here exhibits emergent behavior not predicted by the separate models. Springer US 2012-07-18 2012 /pmc/articles/PMC3463790/ /pubmed/22805979 http://dx.doi.org/10.1007/s10439-012-0611-7 Text en © The Author(s) 2012 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Article Beard, Daniel A. Neal, Maxwell L. Tabesh-Saleki, Nazanin Thompson, Christopher T. Bassingtwaighte, James B. Shimoyama, Mary Carlson, Brian E. Multiscale Modeling and Data Integration in the Virtual Physiological Rat Project |
title | Multiscale Modeling and Data Integration in the Virtual Physiological Rat Project |
title_full | Multiscale Modeling and Data Integration in the Virtual Physiological Rat Project |
title_fullStr | Multiscale Modeling and Data Integration in the Virtual Physiological Rat Project |
title_full_unstemmed | Multiscale Modeling and Data Integration in the Virtual Physiological Rat Project |
title_short | Multiscale Modeling and Data Integration in the Virtual Physiological Rat Project |
title_sort | multiscale modeling and data integration in the virtual physiological rat project |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463790/ https://www.ncbi.nlm.nih.gov/pubmed/22805979 http://dx.doi.org/10.1007/s10439-012-0611-7 |
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