Package: rQSAR 1.0.0
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:
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 = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 months agofrom:5fcc3a1572. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 29 2024 |
R-4.5-linux | OK | Nov 29 2024 |
Exports:build_qsar_modelscorrelation_plotsgenerate_descriptors_from_sdfperform_variable_selectionresidual_plots
Dependencies:caretclasscliclockcodetoolscolorspacecorrplotcpp11data.tablediagramdigestdplyre1071fansifarverfingerprintforeachfuturefuture.applygenericsggplot2globalsgluegowergridExtragtablehardhatipredisobanditeratorsitertoolsKernSmoothlabelinglatticelavaleapslifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplsplyrpngpROCprodlimprogressrproxypurrrR6randomForestrcdkrcdklibsRColorBrewerRcpprecipesreshape2rJavarlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Build QSAR models with k-fold cross-validation | build_qsar_models |
Create correlation plots for QSAR models | correlation_plots |
Generate Molecular Descriptors from SDF File | generate_descriptors_from_sdf |
Perform variable selection using regression subsets | perform_variable_selection |
Function to create residual plots with model type labels | residual_plots |