QSAR Modeling with Multiple Algorithms: MLR, PLS, and Random Forest
Build QSAR models with k-fold cross-validation
Create correlation plots for QSAR models
Generate Molecular Descriptors from SDF File
Perform variable selection using regression subsets
Function to create residual plots with model type labels
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.