dMod2/DESCRIPTION at master · dModverse/dMod2 · GitHub

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Package: dMod2
Type: Package
Title: Dynamic Modeling and Parameter Estimation in ODE Models
Version: 0.12.3
Date: 2026-10-14
Authors@R: c(
    person("Simon", "Beyer", email = "simon.beyer@fdm.uni-freiburg.de",
           role = c("aut", "cre")),
    person("Daniel", "Kaschek", email = "daniel.kaschek@gmail.com",
           role = c("aut", "cph"),
           comment = "Created dMod 1.0; original design, philosophy"),
    person("Daniel", "Lill", email = "daniel.lill@posteo.de", role = "ctb"),
    person("Wolfgang", "Mader", email = "Wolfgang.Mader@fdm.uni-freiburg.de",
           role = "ctb"),
    person("Mirjam", "Fehling-Kaschek",
           email = "mirjam.fehling@physik.uni-freiburg.de", role = "ctb"),
    person("Severin", "Bang", email = "severin.bang@physik.uni-freiburg.de",
           role = "ctb"),
    person("Marcus", "Rosenblatt", email = "marcus.rosenblatt@gmail.com",
           role = "ctb"),
    person("Svenja", "Kemmer", email = "svenja.kemmer@fdm.uni-freiburg.de",
           role = "ctb"),
    person("John", "Fox", role = "ctb",
           comment = "Signature and argument check of rref()"))
Description: Tools for dynamic modeling and parameter estimation in ordinary
    differential equation (ODE) models of reaction networks. Models are built
    symbolically and compiled to C/C++ with first- and second-order
    sensitivities. Prediction, observation and objective functions are
    composable function objects with their symbolic derivatives, following the
    paradigm that derivative information should be used for optimization
    whenever possible. Model calibration uses trust-region optimization with
    optional L1 penalties, multi-start search and profile-likelihood
    identifiability analysis, over experimental conditions that are integrated
    and evaluated in parallel. Further tools cover symbolic steady states,
    parameter transformations with implicit and steady-state solutions, error
    models, and distributed computing on a cluster. Models, experimental
    conditions, measurements and parameter tables are imported from and
    exported to the 'PEtab' format, with 'SBML' import and export through
    'libSBML'.
URL: https://github.com/dModverse/dMod2
BugReports: https://github.com/dModverse/dMod2/issues
License: GPL (>= 2)
Depends: R (>= 4.5.0)
Imports:
    cOde,
    tools,
    cppDE (>= 0.13.0),
    ggplot2,
    parallel,
    stringr,
    dplyr,
    foreach,
    doParallel,
    rlang,
    data.table,
    tidyselect,
    abind,
    Rcpp,
    digest,
    scales,
    grDevices,
    MASS,
    Matrix
Remotes:
    dModverse/cppDE,
    dkaschek/cOde
Suggests:
    jsonlite,
    knitr,
    rmarkdown,
    testthat (>= 3.0.0),
    numDeriv,
    withr,
    deSolve,
    openxlsx,
    Polychrome,
    reticulate,
    lpSolve,
    optimx,
    cowplot,
    pander,
    purrr,
    R.rsp,
    ragg,
    rjson,
    yaml
SystemRequirements: Python package symident (symmetryDetection(),
    symmetryReduction()), installed from PyPI on first use
VignetteBuilder: R.rsp
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
LinkingTo:
    Rcpp
Config/roxygen2/version: 8.1.0
Config/testthat/edition: 3
Config/testthat/parallel: true
Config/testthat/start-first: petab-published, petab-roundtrip, multipleShooting,
    loadDLL, Xs, reverse, compile-chunked, normL2, Y