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EpiSemble  

Ensemble Based Machine Learning Approach for Predicting Methylation States
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("EpiSemble", "0.1.1")



Attach the package and use:
library("EpiSemble")
Maintained by
Dipro Sinha
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-08-22
Latest Update: 2023-06-04
Description:
DNA methylation (6mA) is a major epigenetic process by which alteration in gene expression took place without changing the DNA sequence. Predicting these sites in-vitro is laborious, time consuming as well as costly. This 'EpiSemble' package is an in-silico pipeline for predicting DNA sequences containing the 6mA sites. It uses an ensemble-based machine learning approach by combining Support Vector Machine (SVM), Random Forest (RF) and Gradient Boosting approach to predict the sequences with 6mA sites in it. This package has been developed by using the concept of Chen et al. (2019) .
How to cite:
Dipro Sinha (2022). EpiSemble: Ensemble Based Machine Learning Approach for Predicting Methylation States. R package version 0.1.1, https://cran.r-project.org/web/packages/EpiSemble. Accessed 26 Aug. 2026.
Previous versions and publish date:
0.1.0 (2022-08-22 17:00), (2026-07-09 08:03)
Other packages that cited EpiSemble R package
View EpiSemble citation profile
Other R packages that EpiSemble depends, imports, suggests or enhances
Complete documentation for EpiSemble
Functions, R codes and Examples using the EpiSemble R package
Some associated functions: ImpFeatures . epiPred . 
Some associated R codes: ImpFeatures.R . epiPred.R .  Full EpiSemble package functions and examples
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