Difference between revisions of "Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis"

Line 1: Line 1:
__NUMBEREDHEADINGS__
 
 
== Paper name ==
 
== Paper name ==
 
Paul Stapor, Fabian Fröhlich, and Jan Hasenauer, [https://doi.org/10.1093/bioinformatics/bty230 Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis], 2018, Bioinformatics, Volume 34, Issue 13, Pages i151–i159
 
Paul Stapor, Fabian Fröhlich, and Jan Hasenauer, [https://doi.org/10.1093/bioinformatics/bty230 Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis], 2018, Bioinformatics, Volume 34, Issue 13, Pages i151–i159
 +
 +
 +
=== Summary ===
 +
In this paper, the performance of multiple optimization approaches for estimating parameters in the context of ODE models in systems biology are investigated.
 +
 +
The following combinations of local and global search strategies were investigated:
 +
* Local methods: Two deterministic optimization approaches (''fmincon'' with adjoint sensitivities vs. ''nl2sol'' with forward sensitivities) vs. gradient-free ''dynamic hill climbing'' vs. ''none'' (=only global)

Revision as of 11:55, 25 February 2020

Paper name

Paul Stapor, Fabian Fröhlich, and Jan Hasenauer, Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis, 2018, Bioinformatics, Volume 34, Issue 13, Pages i151–i159


Summary

In this paper, the performance of multiple optimization approaches for estimating parameters in the context of ODE models in systems biology are investigated.

The following combinations of local and global search strategies were investigated:

  • Local methods: Two deterministic optimization approaches (fmincon with adjoint sensitivities vs. nl2sol with forward sensitivities) vs. gradient-free dynamic hill climbing vs. none (=only global)