source · discovered

TSSNote-CyaPromBERT: Development of an integrated platform for highly accurate promoter prediction and visualization of Synechococcus sp. and Synechocystis sp. through a state-of-the-art natural language processing model BERT

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

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Technical metadata and extraction receipts

Stable ID: cyaprombert-2022

areas: microbes-communities
url: https://pmc.ncbi.nlm.nih.gov/articles/PMC9745317/
version: version of record
retrieved at: 2026-09-15T23:25:00Z
doi: 10.3389/fgene.2022.1067562
publication status: peer_reviewed
year: 2022
artifact sha256: 74278ccd77b2bc00a3f4434546545e8bdec8b0652a0e5d1862ec0f91decccd8d
artifact url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC9745317/fullTextXML
artifact retrieved at: 2026-09-16T10:41:16.544033+00:00
legacy paper: id: cyaprombert-2022; title: TSSNote-CyaPromBERT: Development of an integrated platform for highly accurate promoter prediction and visualization of Synechococcus sp. and Synechocystis sp. through a state-of-the-art natural language processing model BERT; year: 2022; publication status: peer_reviewed; version: version of record; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC9745317/; primary domain: microbes-communities; retrieved utc: 2026-09-15T23:25:00Z; notes: Primary full text via Europe PMC XML; venue: Frontiers in Genetics; PMC ID: PMC9745317.; doi: 10.3389/fgene.2022.1067562
scope decision: included
missing metadata: licence: not_reported_in_legacy_extract

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