Package: rQSAR 1.0.0

Oche Ambrose George

rQSAR: QSAR Modeling with Multiple Algorithms: MLR, PLS, and Random Forest

Quantitative Structure-Activity Relationship (QSAR) modeling is a valuable tool in computational chemistry and drug design, where it aims to predict the activity or property of chemical compounds based on their molecular structure. In this vignette, we present the 'rQSAR' package, which provides functions for variable selection and QSAR modeling using Multiple Linear Regression (MLR), Partial Least Squares (PLS), and Random Forest algorithms.

Authors:Oche Ambrose George [aut, cre]

rQSAR_1.0.0.tar.gz
rQSAR_1.0.0.tar.gz(r-4.5-noble)rQSAR_1.0.0.tar.gz(r-4.4-noble)
rQSAR_1.0.0.tgz(r-4.4-emscripten)rQSAR_1.0.0.tgz(r-4.3-emscripten)
rQSAR.pdf |rQSAR.html✨
rQSAR/json (API)

# Install 'rQSAR' in R:
install.packages('rQSAR', repos = 'https://cloud.r-project.org')
Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openjdk

2.00 score 153 downloads 5 exports 87 dependencies

Last updated 1 years agofrom:5fcc3a1572. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 29 2025
R-4.5-linuxOKMar 29 2025
R-4.4-linuxOKMar 29 2025

Exports:build_qsar_modelscorrelation_plotsgenerate_descriptors_from_sdfperform_variable_selectionresidual_plots

Dependencies:caretclasscliclockcodetoolscolorspacecorrplotcpp11data.tablediagramdigestdplyre1071fansifarverfingerprintforeachfuturefuture.applygenericsggplot2globalsgluegowergridExtragtablehardhatipredisobanditeratorsitertoolsKernSmoothlabelinglatticelavaleapslifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplsplyrpngpROCprodlimprogressrproxypurrrR6randomForestrcdkrcdklibsRColorBrewerRcpprecipesreshape2rJavarlangrpartscalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr

QSAR Workflow

George Oche Ambrose

Rendered fromQSAR-Workflow.Rmdusingknitr::rmarkdownon Mar 29 2025.

Last update: 2024-04-03
Started: 2024-04-03

Citation

To cite package ‘rQSAR’ in publications use:

George O (2024). rQSAR: QSAR Modeling with Multiple Algorithms: MLR, PLS, and Random Forest. R package version 1.0.0, https://CRAN.R-project.org/package=rQSAR.

Corresponding BibTeX entry: 

  @Manual{,
    title = {rQSAR: QSAR Modeling with Multiple Algorithms: MLR, PLS,
      and Random Forest},
    author = {Oche Ambrose George},
    year = {2024},
    note = {R package version 1.0.0},
    url = {https://CRAN.R-project.org/package=rQSAR},
  }