PESTO: Parameter EStimation TOolbox

SUMMARY: PESTO is a widely applicable and highly customizable toolbox for parameter estimation in MathWorks MATLAB. It offers scalable algorithms for optimization, uncertainty and identifiability analysis, which work in a very generic manner, treating the objective function as a black box. Hence, PE...

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Autores principales: Stapor, Paul, Weindl, Daniel, Ballnus, Benjamin, Hug, Sabine, Loos, Carolin, Fiedler, Anna, Krause, Sabrina, Hroß, Sabrina, Fröhlich, Fabian, Hasenauer, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860618/
https://www.ncbi.nlm.nih.gov/pubmed/29069312
http://dx.doi.org/10.1093/bioinformatics/btx676
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author Stapor, Paul
Weindl, Daniel
Ballnus, Benjamin
Hug, Sabine
Loos, Carolin
Fiedler, Anna
Krause, Sabrina
Hroß, Sabrina
Fröhlich, Fabian
Hasenauer, Jan
author_facet Stapor, Paul
Weindl, Daniel
Ballnus, Benjamin
Hug, Sabine
Loos, Carolin
Fiedler, Anna
Krause, Sabrina
Hroß, Sabrina
Fröhlich, Fabian
Hasenauer, Jan
author_sort Stapor, Paul
collection PubMed
description SUMMARY: PESTO is a widely applicable and highly customizable toolbox for parameter estimation in MathWorks MATLAB. It offers scalable algorithms for optimization, uncertainty and identifiability analysis, which work in a very generic manner, treating the objective function as a black box. Hence, PESTO can be used for any parameter estimation problem, for which the user can provide a deterministic objective function in MATLAB. AVAILABILITY AND IMPLEMENTATION: PESTO is a MATLAB toolbox, freely available under the BSD license. The source code, along with extensive documentation and example code, can be downloaded from https://github.com/ICB-DCM/PESTO/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-58606182018-03-28 PESTO: Parameter EStimation TOolbox Stapor, Paul Weindl, Daniel Ballnus, Benjamin Hug, Sabine Loos, Carolin Fiedler, Anna Krause, Sabrina Hroß, Sabrina Fröhlich, Fabian Hasenauer, Jan Bioinformatics Applications Notes SUMMARY: PESTO is a widely applicable and highly customizable toolbox for parameter estimation in MathWorks MATLAB. It offers scalable algorithms for optimization, uncertainty and identifiability analysis, which work in a very generic manner, treating the objective function as a black box. Hence, PESTO can be used for any parameter estimation problem, for which the user can provide a deterministic objective function in MATLAB. AVAILABILITY AND IMPLEMENTATION: PESTO is a MATLAB toolbox, freely available under the BSD license. The source code, along with extensive documentation and example code, can be downloaded from https://github.com/ICB-DCM/PESTO/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-02-15 2017-10-23 /pmc/articles/PMC5860618/ /pubmed/29069312 http://dx.doi.org/10.1093/bioinformatics/btx676 Text en © The Author 2017. 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 Applications Notes
Stapor, Paul
Weindl, Daniel
Ballnus, Benjamin
Hug, Sabine
Loos, Carolin
Fiedler, Anna
Krause, Sabrina
Hroß, Sabrina
Fröhlich, Fabian
Hasenauer, Jan
PESTO: Parameter EStimation TOolbox
title PESTO: Parameter EStimation TOolbox
title_full PESTO: Parameter EStimation TOolbox
title_fullStr PESTO: Parameter EStimation TOolbox
title_full_unstemmed PESTO: Parameter EStimation TOolbox
title_short PESTO: Parameter EStimation TOolbox
title_sort pesto: parameter estimation toolbox
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860618/
https://www.ncbi.nlm.nih.gov/pubmed/29069312
http://dx.doi.org/10.1093/bioinformatics/btx676
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