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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 and Akman, Ozgur E., et al. (2013) In Bioinformatics 29(5). p.664-665
Abstract
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;... (More)
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. (Less)
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type
Contribution to journal
publication status
published
subject
in
Bioinformatics
volume
29
issue
5
pages
664 - 665
publisher
Oxford University Press
external identifiers
  • wos:000315623000022
  • scopus:84874737603
ISSN
1367-4803
DOI
10.1093/bioinformatics/btt023
language
English
LU publication?
no
id
18b1c0fa-5108-4852-9c89-afe793ddc5e2 (old id 3670002)
date added to LUP
2013-04-23 14:47:26
date last changed
2019-07-09 01:04:06
@article{18b1c0fa-5108-4852-9c89-afe793ddc5e2,
  abstract     = {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.},
  author       = {Adams, Richard and Clark, Allan and Yamaguchi, Azusa and Hanlon, Neil and Tsorman, Nikos and Ali, Shakir and Lebedeva, Galina and Goltsov, Alexey and Sorokin, Anatoly and Akman, Ozgur E. and Troein, Carl and Millar, Andrew J. and Goryanin, Igor and Gilmore, Stephen},
  issn         = {1367-4803},
  language     = {eng},
  number       = {5},
  pages        = {664--665},
  publisher    = {Oxford University Press},
  series       = {Bioinformatics},
  title        = {SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology},
  url          = {http://dx.doi.org/10.1093/bioinformatics/btt023},
  volume       = {29},
  year         = {2013},
}