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GB5mcPred  

Gradient Boosting Algorithm for Predicting Methylation States
View on CRAN: Click here


Download and install GB5mcPred package within the R console
Install from CRAN:
install.packages("GB5mcPred")

Install from Github:
library("remotes")
install_github("cran/GB5mcPred")

Install by package version:
library("remotes")
install_version("GB5mcPred", "0.1.0")



Attach the package and use:
library("GB5mcPred")
Maintained by
Dipro Sinha
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-07-11
Latest Update: 2023-07-11
Description:
DNA methylation of 5-methylcytosine (5mC) is the result of a multi-step, enzyme-dependent process. Predicting these sites in-vitro is laborious, time consuming as well as costly. This ' Gb5mC-Pred ' package is an in-silico pipeline for predicting DNA sequences containing the 5mC sites. It uses a machine learning approach which uses Stochastic Gradient Boosting approach for prediction of the sequences with 5mC sites. This package has been developed by using the concept of Navarez and Roxas (2022) .
How to cite:
Dipro Sinha (2023). GB5mcPred: Gradient Boosting Algorithm for Predicting Methylation States. R package version 0.1.0, https://cran.r-project.org/web/packages/GB5mcPred. Accessed 18 Sep. 2026.
Previous versions and publish date:
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Complete documentation for GB5mcPred
Functions, R codes and Examples using the GB5mcPred R package
Full GB5mcPred package functions and examples
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