Abstract
The software provides machine learning analysis and visualization to detect patterns in epigenetic data, including conventional machine learning and statistical methods, and open-source packages like pyBigWig (https://github.com/deeptools/pyBigWig) for data processing. The software is written in python, it uses some python libraries.
- Developers:
- Release Date:
- 2024-07-23
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Licenses:
-
BSD 3-clause "New" or "Revised" License
- Sponsoring Org.:
-
USDOEPrimary Award/Contract Number:AC52-06NA25396
- Code ID:
- 140140
- Site Accession Number:
- O4747
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Country of Origin:
- United States
Citation Formats
Kim, Anastasiia.
Machine learning tools for epigenetics.
Computer Software.
https://github.com/lanl/epigen.
USDOE.
23 Jul. 2024.
Web.
doi:10.11578/dc.20240809.10.
Kim, Anastasiia.
(2024, July 23).
Machine learning tools for epigenetics.
[Computer software].
https://github.com/lanl/epigen.
https://doi.org/10.11578/dc.20240809.10.
Kim, Anastasiia.
"Machine learning tools for epigenetics." Computer software.
July 23, 2024.
https://github.com/lanl/epigen.
https://doi.org/10.11578/dc.20240809.10.
@misc{
doecode_140140,
title = {Machine learning tools for epigenetics},
author = {Kim, Anastasiia},
abstractNote = {The software provides machine learning analysis and visualization to detect patterns in epigenetic data, including conventional machine learning and statistical methods, and open-source packages like pyBigWig (https://github.com/deeptools/pyBigWig) for data processing. The software is written in python, it uses some python libraries.},
doi = {10.11578/dc.20240809.10},
url = {https://doi.org/10.11578/dc.20240809.10},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240809.10}},
year = {2024},
month = {jul}
}