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WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions
Mechanistic ‘whole-cell’ models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165886/ https://www.ncbi.nlm.nih.gov/pubmed/25231498 http://dx.doi.org/10.1093/database/bau095 |
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author | Karr, Jonathan R. Phillips, Nolan C. Covert, Markus W. |
author_facet | Karr, Jonathan R. Phillips, Nolan C. Covert, Markus W. |
author_sort | Karr, Jonathan R. |
collection | PubMed |
description | Mechanistic ‘whole-cell’ models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations. WholeCellSimDB was designed to enable researchers to search simulation metadata to identify simulations for further analysis, and quickly slice and aggregate simulation results data. In addition, WholeCellSimDB enables users to share simulations with the broader research community. The database uses a hybrid relational/hierarchical data format architecture to efficiently store and retrieve both simulation setup metadata and results data. WholeCellSimDB provides a graphical Web-based interface to search, browse, plot and export simulations; a JavaScript Object Notation (JSON) Web service to retrieve data for Web-based visualizations; a command-line interface to deposit simulations; and a Python API to retrieve data for advanced analysis. Overall, we believe WholeCellSimDB will help researchers use whole-cell models to advance basic biological science and bioengineering. Database URL: http://www.wholecellsimdb.org Source code repository URL: http://github.com/CovertLab/WholeCellSimDB |
format | Online Article Text |
id | pubmed-4165886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41658862014-09-22 WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions Karr, Jonathan R. Phillips, Nolan C. Covert, Markus W. Database (Oxford) Database Tool Mechanistic ‘whole-cell’ models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations. WholeCellSimDB was designed to enable researchers to search simulation metadata to identify simulations for further analysis, and quickly slice and aggregate simulation results data. In addition, WholeCellSimDB enables users to share simulations with the broader research community. The database uses a hybrid relational/hierarchical data format architecture to efficiently store and retrieve both simulation setup metadata and results data. WholeCellSimDB provides a graphical Web-based interface to search, browse, plot and export simulations; a JavaScript Object Notation (JSON) Web service to retrieve data for Web-based visualizations; a command-line interface to deposit simulations; and a Python API to retrieve data for advanced analysis. Overall, we believe WholeCellSimDB will help researchers use whole-cell models to advance basic biological science and bioengineering. Database URL: http://www.wholecellsimdb.org Source code repository URL: http://github.com/CovertLab/WholeCellSimDB Oxford University Press 2014-09-16 /pmc/articles/PMC4165886/ /pubmed/25231498 http://dx.doi.org/10.1093/database/bau095 Text en © The Author(s) 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Tool Karr, Jonathan R. Phillips, Nolan C. Covert, Markus W. WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions |
title | WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions |
title_full | WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions |
title_fullStr | WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions |
title_full_unstemmed | WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions |
title_short | WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions |
title_sort | wholecellsimdb: a hybrid relational/hdf database for whole-cell model predictions |
topic | Database Tool |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165886/ https://www.ncbi.nlm.nih.gov/pubmed/25231498 http://dx.doi.org/10.1093/database/bau095 |
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