seeds: 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) <doi:10.1038/srep20772>. To use the experimental SBML import function, the 'rsbml' package is required. For installation I refer to the official 'rsbml' page: <https://bioconductor.org/packages/release/bioc/html/rsbml.html>.

Version: 0.9.0
Depends: R (≥ 3.5.0)
Imports: deSolve (≥ 1.20), pracma (≥ 2.1.4), Deriv (≥ 3.8.4), Ryacas, stats, graphics, methods, mvtnorm, matrixStats, statmod, coda, MASS, ggplot2, tidyr, dplyr, Hmisc, R.utils, callr
Suggests: rsbml, knitr, rmarkdown
Published: 2020-03-20
Author: Tobias Newmiwaka [aut, cre], Benjamin Engelhardt [aut]
Maintainer: Tobias Newmiwaka <tobias.newmiwaka at gmail.com>
BugReports: https://github.com/Newmi1988/seeds/issues
License: MIT + file LICENSE
URL: https://github.com/Newmi1988/seeds
NeedsCompilation: no
CRAN checks: seeds results

Downloads:

Reference manual: seeds.pdf
Vignettes: Seeds: Calculating the hidden inputs in a system
Package source: seeds_0.9.0.tar.gz
Windows binaries: r-devel: seeds_0.9.0.zip, r-devel-gcc8: seeds_0.9.0.zip, r-release: seeds_0.9.0.zip, r-oldrel: seeds_0.9.0.zip
OS X binaries: r-release: seeds_0.9.0.tgz, r-oldrel: seeds_0.9.0.tgz

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