source · discovered

Structure-Informed Protein Language Models are Robust Predictors for Variant Effects

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: structure-informed-plm-2025

areas: proteins-complexes
url: https://pmc.ncbi.nlm.nih.gov/articles/PMC12068927/
version: Human Genetics 2025 journal article (online 2024)
retrieved at: 2026-09-15T23:33:26Z
doi: 10.1007/s00439-024-02695-w
publication status: peer_reviewed
year: 2025
artifact sha256: 76082e1cd992d2c09c38f86d05aba575cc76c5022b53a297123b713bb1ce9267
artifact url: https://pmc.ncbi.nlm.nih.gov/articles/PMC12068927/
artifact retrieved at: 2026-09-16T10:45:41.099916+00:00
legacy paper: id: structure-informed-plm-2025; title: Structure-Informed Protein Language Models are Robust Predictors for Variant Effects; year: 2025; publication status: peer_reviewed; version: Human Genetics 2025 journal article (online 2024); source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC12068927/; primary domain: proteins-complexes; retrieved utc: 2026-09-15T23:33:26Z; doi: 10.1007/s00439-024-02695-w; notes: Final Human Genetics Table 4, AA+SS+RSA+CM AUROC .803 checked directly; Research Square preprint Table 3 prints the same value.
scope decision: included
missing metadata: licence: not_reported_in_legacy_extract

Related records