Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Deep learning framework for RNA 5hmC prediction using RNA language model embeddings

Saved in:
Bibliographic Details
Published in:PLOS ONE
Format: Online Article RSS Article
Published: 2026
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1864030190701641731
collection WordPress RSS
FRELIP Feed Integration
container_title PLOS ONE
description
discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
RSS Article
genre Journal Article
id rss_article:8203
institution FRELIP
journal_source_facet PLOS ONE
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Deep learning framework for RNA 5hmC prediction using RNA language model embeddings
Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
subject_facet Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
title Deep learning framework for RNA 5hmC prediction using RNA language model embeddings
title_auth Deep learning framework for RNA 5hmC prediction using RNA language model embeddings
title_full Deep learning framework for RNA 5hmC prediction using RNA language model embeddings
title_fullStr Deep learning framework for RNA 5hmC prediction using RNA language model embeddings
title_full_unstemmed Deep learning framework for RNA 5hmC prediction using RNA language model embeddings
title_short Deep learning framework for RNA 5hmC prediction using RNA language model embeddings
title_sort deep learning framework for rna 5hmc prediction using rna language model embeddings
topic Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
url https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0341649