Published September 12, 2023
| Version v1
Software
Open
MalariaSED
Description
MalariaSED is a sequence-based Deep Learning (DL) framework in malaria parasites to understand the contribution of noncoding variants to epigenetic profiles. The current version is able to predict the chromatin impacts, including open chromatin accessibility, H3K9ac, and six TFs, including PfAP2-G, PfAP2-I, PfBDP1, PfAP2-G5, PbAP2-O, and PbAP2-G2, covering different parasite living environments like the mosquito host, the human liver, and human blood cells.
Files
MalariaSED-master.zip
Files
(857.4 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/CharleyWang/MalariaSED (URL)