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rQSAR  

QSAR Modeling with Multiple Algorithms: MLR, PLS, and Random Forest
View on CRAN: Click here


Download and install rQSAR package within the R console
Install from CRAN:
install.packages("rQSAR")

Install from Github:
library("remotes")
install_github("cran/rQSAR")

Install by package version:
library("remotes")
install_version("rQSAR", "1.0.0")



Attach the package and use:
library("rQSAR")
Maintained by
Oche Ambrose George
[Scholar Profile | Author Map]
First Published: 2024-04-02
Latest Update: 2024-04-02
Description:
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.
How to cite:
Oche Ambrose George (2024). rQSAR: QSAR Modeling with Multiple Algorithms: MLR, PLS, and Random Forest. R package version 1.0.0, https://cran.r-project.org/web/packages/rQSAR. Accessed 17 Feb. 2025.
Previous versions and publish date:
No previous versions
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View rQSAR citation profile
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Complete documentation for rQSAR
Functions, R codes and Examples using the rQSAR R package
Full rQSAR package functions and examples
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