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pyPESTO: a modular and scalable tool for parameter estimation for dynamic models.
Schälte, Yannik; Fröhlich, Fabian; Jost, Paul J; Vanhoefer, Jakob; Pathirana, Dilan; Stapor, Paul; Lakrisenko, Polina; Wang, Dantong; Raimúndez, Elba; Merkt, Simon; Schmiester, Leonard; Städter, Philipp; Grein, Stephan; Dudkin, Erika; Doresic, Domagoj; Weindl, Daniel; Hasenauer, Jan.
Afiliação
  • Schälte Y; Life and Medical Sciences (LIMES) Institute, University of Bonn, 53113 Bonn, Germany.
  • Fröhlich F; Computational Health Center, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), 85764 Neuherberg, Germany.
  • Jost PJ; Department of Mathematics, Technical University of Munich, 85748 Garching, Germany.
  • Vanhoefer J; Department of Systems Biology, Harvard Medical School, Boston, MA 02115, United States.
  • Pathirana D; Life and Medical Sciences (LIMES) Institute, University of Bonn, 53113 Bonn, Germany.
  • Stapor P; Life and Medical Sciences (LIMES) Institute, University of Bonn, 53113 Bonn, Germany.
  • Lakrisenko P; Life and Medical Sciences (LIMES) Institute, University of Bonn, 53113 Bonn, Germany.
  • Wang D; Computational Health Center, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), 85764 Neuherberg, Germany.
  • Raimúndez E; Department of Mathematics, Technical University of Munich, 85748 Garching, Germany.
  • Merkt S; Computational Health Center, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), 85764 Neuherberg, Germany.
  • Schmiester L; School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.
  • Städter P; Computational Health Center, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), 85764 Neuherberg, Germany.
  • Grein S; Department of Mathematics, Technical University of Munich, 85748 Garching, Germany.
  • Dudkin E; Life and Medical Sciences (LIMES) Institute, University of Bonn, 53113 Bonn, Germany.
  • Doresic D; Computational Health Center, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), 85764 Neuherberg, Germany.
  • Weindl D; Department of Mathematics, Technical University of Munich, 85748 Garching, Germany.
  • Hasenauer J; Life and Medical Sciences (LIMES) Institute, University of Bonn, 53113 Bonn, Germany.
Bioinformatics ; 39(11)2023 11 01.
Article em En | MEDLINE | ID: mdl-37995297
ABSTRACT

SUMMARY:

Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challenging for large and complex systems. pyPESTO is a modular framework for systematic parameter estimation, with scalable algorithms for optimization and uncertainty quantification. While tailored to ordinary differential equation problems, pyPESTO is broadly applicable to black-box parameter estimation problems. Besides own implementations, it provides a unified interface to various popular simulation and inference methods. AVAILABILITY AND IMPLEMENTATION pyPESTO is implemented in Python, open-source under a 3-Clause BSD license. Code and documentation are available on GitHub (https//github.com/icb-dcm/pypesto).
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Software Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Software Idioma: En Ano de publicação: 2023 Tipo de documento: Article