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http://krishi.icar.gov.in/jspui/handle/123456789/76542| Title: | R-package EpiSemble: Ensemble Based Machine Learning Approach for Predicting Methylation States |
| Other Titles: | Not Available |
| Authors: | Dipro Sinha, Sunil Archak, Dwijesh Chandra Mishra, Tanwy Dasmandal, Md Yeasin |
| ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
| Author's Affiliated institute: | ICAR::National Bureau of Plant Genetics Resources ICAR::Indian Agricultural Statistics Research Institute |
| Published/ Complete Date: | 2022-10-01 |
| Project Code: | Not Available |
| Keywords: | R-package |
| Publisher: | Not Available |
| Citation: | Not Available |
| Series/Report no.: | Not Available; |
| Abstract/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) |
| Description: | Not Available |
| ISSN: | Not Available |
| Type(s) of content: | Software Code or Macro |
| Sponsors: | Not Available |
| Language: | English |
| Name of Journal: | Not Available |
| Volume No.: | Not Available |
| Page Number: | Not Available |
| Name of the Division/Regional Station: | Not Available |
| Source, DOI or any other URL: | https://CRAN.R-project.org/package=EpiSemble |
| URI: | http://krishi.icar.gov.in/jspui/handle/123456789/76542 |
| Appears in Collections: | AEdu-IASRI-Publication |
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