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.
Version: 1.0.0 Depends: R (≥ 3.6.0), dplyr, corrplot, tibble, gridExtra Imports: utils, rcdk (≥ 3.8.1), ggplot2, caret, pls, randomForest, leaps, stats Suggests: rmarkdown, knitr Published: 2024-04-02 DOI: 10.32614/CRAN.package.rQSAR Author: Oche Ambrose George [aut, cre] Maintainer: Oche Ambrose George <ocheab1 at gmail.com> License: MIT + file LICENSE NeedsCompilation: no CRAN checks: rQSAR results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=rQSAR to link to this page.
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