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seeds

Estimate Hidden Inputs using the Dynamic Elastic Net

Installation

About

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: .

github.com/Newmi1988/seeds
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Key Metrics

Version 0.9.1
R ≥ 3.5.0
Published 2020-07-14 1388 days ago
Needs compilation? no
License MIT
License File
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Maintainer

Maintainer

Tobias Newmiwaka

tobias.newmiwaka@gmail.com

Authors

Tobias Newmiwaka

aut / cre

Benjamin Engelhardt

aut

Material

Reference manual
Package source

Vignettes

Seeds: Calculating the hidden inputs in a system

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

seeds archive

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

knitr
rmarkdown
rsbml