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DrugClust  

Implementation of a Machine Learning Framework for Predicting Drugs Side Effects
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("DrugClust", "0.2")



Attach the package and use:
library("DrugClust")
Maintained by
Giovanna Maria Dimitri
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-01-19
Latest Update: 2023-08-18
Description:
An implementation of a Machine Learning Framework for prediction of new drugs Side Effects. Firstly drugs are clustered with respect to their features description and secondly predictions are made, according to Bayesian scores. Moreover it can perform protein enrichment considering the proteins clustered together in the first step of the algorithm. This last tool is of extreme interest for biologist and drug discovery purposes, given the fact that it can be used either as a validation of the clusters obtained, as well as for the possible discovery of new interactions between certain side effects and non targeted pathways. Clustering of the drugs in the feature space can be done using K-Means, PAM or K-Seeds (a novel clustering algorithm proposed by the author).
How to cite:
Giovanna Maria Dimitri (2016). DrugClust: Implementation of a Machine Learning Framework for Predicting Drugs Side Effects. R package version 0.2, https://cran.r-project.org/web/packages/DrugClust. Accessed 28 Mar. 2025.
Previous versions and publish date:
0.1 (2016-01-19 18:22), 0.2 (2016-04-23 14:19)
Other packages that cited DrugClust R package
View DrugClust citation profile
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