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SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology
Summary: Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3582266/ https://www.ncbi.nlm.nih.gov/pubmed/23329415 http://dx.doi.org/10.1093/bioinformatics/btt023 |
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author | Adams, Richard Clark, Allan Yamaguchi, Azusa Hanlon, Neil Tsorman, Nikos Ali, Shakir Lebedeva, Galina Goltsov, Alexey Sorokin, Anatoly Akman, Ozgur E. Troein, Carl Millar, Andrew J. Goryanin, Igor Gilmore, Stephen |
author_facet | Adams, Richard Clark, Allan Yamaguchi, Azusa Hanlon, Neil Tsorman, Nikos Ali, Shakir Lebedeva, Galina Goltsov, Alexey Sorokin, Anatoly Akman, Ozgur E. Troein, Carl Millar, Andrew J. Goryanin, Igor Gilmore, Stephen |
author_sort | Adams, Richard |
collection | PubMed |
description | Summary: Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting; SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers; and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSI’s use of standard data formats. Availability and implementation: All SBSI binaries and source-code are freely available from http://sourceforge.net/projects/sbsi under an Apache 2 open-source license. The server-side SBSINumerics runs on any Unix-based operating system; both SBSIVisual and SBSIDispatcher are written in Java and are platform independent, allowing use on Windows, Linux and Mac OS X. The SBSI project website at http://www.sbsi.ed.ac.uk provides documentation and tutorials. Contact: stg@inf.ed.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-3582266 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-35822662013-02-26 SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology Adams, Richard Clark, Allan Yamaguchi, Azusa Hanlon, Neil Tsorman, Nikos Ali, Shakir Lebedeva, Galina Goltsov, Alexey Sorokin, Anatoly Akman, Ozgur E. Troein, Carl Millar, Andrew J. Goryanin, Igor Gilmore, Stephen Bioinformatics Applications Notes Summary: Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting; SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers; and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSI’s use of standard data formats. Availability and implementation: All SBSI binaries and source-code are freely available from http://sourceforge.net/projects/sbsi under an Apache 2 open-source license. The server-side SBSINumerics runs on any Unix-based operating system; both SBSIVisual and SBSIDispatcher are written in Java and are platform independent, allowing use on Windows, Linux and Mac OS X. The SBSI project website at http://www.sbsi.ed.ac.uk provides documentation and tutorials. Contact: stg@inf.ed.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2013-03-01 2013-01-17 /pmc/articles/PMC3582266/ /pubmed/23329415 http://dx.doi.org/10.1093/bioinformatics/btt023 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Adams, Richard Clark, Allan Yamaguchi, Azusa Hanlon, Neil Tsorman, Nikos Ali, Shakir Lebedeva, Galina Goltsov, Alexey Sorokin, Anatoly Akman, Ozgur E. Troein, Carl Millar, Andrew J. Goryanin, Igor Gilmore, Stephen SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology |
title | SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology |
title_full | SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology |
title_fullStr | SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology |
title_full_unstemmed | SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology |
title_short | SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology |
title_sort | sbsi: an extensible distributed software infrastructure for parameter estimation in systems biology |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3582266/ https://www.ncbi.nlm.nih.gov/pubmed/23329415 http://dx.doi.org/10.1093/bioinformatics/btt023 |
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