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.


Reference manual

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install.packages("rQSAR")

1.0.0 by Oche Ambrose George, 3 years ago


Browse source code at https://github.com/cran/rQSAR


Authors: Oche Ambrose George [aut, cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports utils, rcdk, ggplot2, caret, pls, randomForest, leaps, stats

Depends on dplyr, corrplot, tibble, gridExtra

Suggests rmarkdown, knitr


See at CRAN