seeds (0.9.0)

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Estimate Hidden Inputs using the Dynamic Elastic Net.

Algorithms to calculate the hidden inputs of systems of differential equations. These hidden inputs can be interpreted as a control that tries to minimize the discrepancies between a given model and taken measurements. The idea is also called the Dynamic Elastic Net, as proposed in the paper "Learning (from) the errors of a systems biology model" (Engelhardt, Froelich, Kschischo 2016) . To use the experimental SBML import function, the 'rsbml' package is required. For installation I refer to the official 'rsbml' page: .

Maintainer: Tobias Newmiwaka
Author(s): Tobias Newmiwaka [aut, cre], Benjamin Engelhardt [aut]

License: MIT + file LICENSE

Uses: callr, coda, Deriv, deSolve, dplyr, ggplot2, Hmisc, MASS, matrixStats, mvtnorm, pracma, R.utils, Ryacas, statmod, tidyr, rsbml, knitr, rmarkdown

Released 2 months ago.



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