source · discovered

Generalizable deep-learning-based mRNA-protein interaction prediction strongly depends on protein diversity

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

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

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Technical metadata and extraction receipts

Stable ID: mrna-protein-diversity-2026

areas: rna-transcriptomes
url: https://pmc.ncbi.nlm.nih.gov/articles/PMC13235059/
version: version of record
retrieved at: 2026-09-15T23:37:05Z
doi: 10.1186/s13321-026-01197-3
publication status: peer_reviewed
year: 2026
artifact sha256: 94f9fe22a5f0e6c8619e4af994eb4f6ded7417efcf0c1240380269280f97f9d1
artifact url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13235059/fullTextXML
artifact retrieved at: 2026-09-16T10:33:57.257Z
legacy paper: id: mrna-protein-diversity-2026; title: Generalizable deep-learning-based mRNA-protein interaction prediction strongly depends on protein diversity; year: 2026; publication status: peer_reviewed; version: version of record; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC13235059/; primary domain: rna-transcriptomes; retrieved utc: 2026-09-15T23:37:05Z; notes: Primary full text verified via Europe PMC fullTextXML; venue: Journal of Cheminformatics; PMC ID: PMC13235059. ProteinBERT encodes the protein side of an mRNA-protein task; score is not an RNA foundation-model result.; doi: 10.1186/s13321-026-01197-3
scope decision: included
missing metadata: licence: not_reported_in_legacy_extract

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