source · discovered

DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning

Primary paper retained with its original identifier. Metadata inherited from the literature collection; individual result checks are separate.

Sources and history

Release 2026-09-16-d74d282221a9 · Record review: discovered

No supporting source is linked yet.

Technical metadata and extraction receipts

Stable ID: debfold-2024

areas: rna-transcriptomes
url: https://pmc.ncbi.nlm.nih.gov/articles/PMC11094721/
version: PMC11094721.1
retrieved at: 2026-09-15T23:25:00Z
doi: 10.1021/acs.jcim.4c00458
publication status: peer_reviewed
year: 2024
artifact sha256: e8f960eafb7f00edfdd81d4fb75c6de838e9b872b7e18875fc7a5bff2a2f72b3
artifact url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC11094721/fullTextXML
artifact retrieved at: 2026-09-16T10:41:16.509290+00:00
legacy paper: id: debfold-2024; title: DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning; year: 2024; publication status: peer_reviewed; version: PMC11094721.1; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC11094721/; primary domain: rna-transcriptomes; retrieved utc: 2026-09-15T23:25:00Z; notes: Primary full text via Europe PMC XML; venue: Journal of Chemical Information and Modeling; PMC ID: PMC11094721.; doi: 10.1021/acs.jcim.4c00458
scope decision: included
missing metadata: licence: not_reported_in_legacy_extract

Related records