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EpiSemble

Ensemble Based Machine Learning Approach for Predicting Methylation States

v0.1.1 · Jun 4, 2023 · GPL-3

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) <doi:10.1093/bioinformatics/btz015>.

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ERROR r-devel-linux-x86_64-debian-clang

package dependencies

Package required but not available: ‘Biostrings’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
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ERROR 13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Mar 9, 2026
ERROR r-devel-linux-x86_64-debian-clang

package dependencies

Package required but not available: ‘Biostrings’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.

Dependency Network

Dependencies Reverse dependencies devtools tidyverse seqinr Biostrings splitstackshape entropy party stringr tibble doParallel e1071 caret randomForest gbm foreach +2 more dependencies EpiSemble

Version History

new 0.1.1 Mar 9, 2026