PESTO: Parameter EStimation TOolbox | Zendy

Paul Stapor | Zendy; Daniel Weindl | Zendy; Benjamin Ballnus | Zendy; Sabine Hug | Zendy; Carolin Loos | Zendy; Anna Fiedler | Zendy; Sabrina Krause | Zendy; Sabrina Hroß | Zendy; Fabian Fröhlich | Zendy; Jan Hasenauer | Zendy

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PESTO: Parameter EStimation TOolbox

Author(s) -

Paul Stapor,

Daniel Weindl,

Benjamin Ballnus,

Sabine Hug,

Carolin Loos,

Anna Fiedler,

Sabrina Krause,

Sabrina Hroß,

Fabian Fröhlich,

Jan Hasenauer

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx676

Subject(s) - toolbox , computer science , estimation , estimation theory , algorithm , programming language , engineering , systems engineering

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.

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