source · discovered

Cell type annotation for scATAC-seq via DNA large language model and graph domain adaptation

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: scatac-llmda-2026

areas: cells-tissues
url: https://pmc.ncbi.nlm.nih.gov/articles/PMC13132462/
version: version of record
retrieved at: 2026-09-15T23:29:32Z
doi: 10.1371/journal.pcbi.1014226
publication status: peer_reviewed
year: 2026
artifact sha256: f1cdc7d54c6b2d491e4a74a44a1188a3679c555262c988e95a1c0de4614fe3cb
artifact url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13132462/fullTextXML
artifact retrieved at: 2026-09-16T10:44:03.395850+00:00
legacy paper: id: scatac-llmda-2026; title: Cell type annotation for scATAC-seq via DNA large language model and graph domain adaptation; year: 2026; publication status: peer_reviewed; version: version of record; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC13132462/; primary domain: cells-tissues; retrieved utc: 2026-09-15T23:29:32Z; notes: Primary full text verified using Europe PMC XML; venue: PLOS Computational Biology; PMC ID: PMC13132462.; doi: 10.1371/journal.pcbi.1014226
scope decision: included
missing metadata: licence: not_reported_in_legacy_extract

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