Nothing
EpiSemble: Ensemble Based Machine Learning Approach for Predicting Methylation States
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) <doi:10.1093/bioinformatics/btz015>.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Dipro Sinha [aut, cre], Sunil Archak [aut], Dwijesh Chandra Mishra [aut], Tanwy Dasmandal [aut], Md Yeasin [aut] |
| Maintainer | Dipro Sinha <diprosinha@gmail.com> |
| License | GPL-3 |
| Version | 0.1.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the EpiSemble package in your browser
Any scripts or data that you put into this service are public.
