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Paul Stapor

Showing results (1-10 of 8) with videos related to

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Bioinformatics (Oxford, England)|June 29, 2018
Optimization and profile calculation of ODE models using second order adjoint sensitivity analysisPaul Stapor, Fabian Fröhlich, Jan Hasenauer
Bioinformatics (Oxford, England)|April 6, 2021
AMICI: high-performance sensitivity analysis for large ordinary differential equation modelsFabian Fröhlich, Daniel Weindl, Yannik Schälte, et al.
Nature Communications|January 11, 2022
Mini-batch optimization enables training of ODE models on large-scale datasetsPaul Stapor, Leonard Schmiester, Christoph Wierling, et al.
Plos Computational Biology|January 3, 2023
Efficient computation of adjoint sensitivities at steady-state in ODE models of biochemical reaction networksPolina Lakrisenko, Paul Stapor, Stephan Grein, et al.
Bioinformatics (Oxford, England)|October 26, 2017
PESTO: Parameter EStimation TOolboxPaul Stapor, Daniel Weindl, Benjamin Ballnus, et al.
Cell Reports|August 11, 2021
Cell-to-cell variability in JAK2/STAT5 pathway components and cytoplasmic volumes defines survival threshold in erythroid progenitor cellsLorenz Adlung, Paul Stapor, Christian Tönsing, et al.
Epidemics|March 17, 2023
Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contactsLorenzo Contento, Noemi Castelletti, Elba Raimúndez, et al.
Bioinformatics (Oxford, England)|November 23, 2023
pyPESTO: a modular and scalable tool for parameter estimation for dynamic modelsYannik Schälte, Fabian Fröhlich, Paul J Jost, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Bioinformatics (Oxford, England)|June 29, 2018
Optimization and profile calculation of ODE models using second order adjoint sensitivity analysisPaul Stapor, Fabian Fröhlich, Jan Hasenauer
Bioinformatics (Oxford, England)|April 6, 2021
AMICI: high-performance sensitivity analysis for large ordinary differential equation modelsFabian Fröhlich, Daniel Weindl, Yannik Schälte, et al.
Nature Communications|January 11, 2022
Mini-batch optimization enables training of ODE models on large-scale datasetsPaul Stapor, Leonard Schmiester, Christoph Wierling, et al.
Plos Computational Biology|January 3, 2023
Efficient computation of adjoint sensitivities at steady-state in ODE models of biochemical reaction networksPolina Lakrisenko, Paul Stapor, Stephan Grein, et al.
Bioinformatics (Oxford, England)|October 26, 2017
PESTO: Parameter EStimation TOolboxPaul Stapor, Daniel Weindl, Benjamin Ballnus, et al.
Cell Reports|August 11, 2021
Cell-to-cell variability in JAK2/STAT5 pathway components and cytoplasmic volumes defines survival threshold in erythroid progenitor cellsLorenz Adlung, Paul Stapor, Christian Tönsing, et al.
Epidemics|March 17, 2023
Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contactsLorenzo Contento, Noemi Castelletti, Elba Raimúndez, et al.
Bioinformatics (Oxford, England)|November 23, 2023
pyPESTO: a modular and scalable tool for parameter estimation for dynamic modelsYannik Schälte, Fabian Fröhlich, Paul J Jost, et al.
Pageof 1