ReadSeeker: A DNABERT based de-novo read-level gene predictor.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 41231910.
- Also identified by DOI 10.1371/journal.pone.0335732 and PMC identifier 12614542.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
ReadSeeker, a newly fine-tuned, DNABERT-based model, differentiates NGS short reads into protein-coding (CDS) and non-protein-coding (non-CDS) categories without requiring known reference sequences. For model training, extensive datasets encompassing viral, bacterial, and mammalian sequences where used. Training involved generating approximately 3 million synthetic reads from annotated genomic elements. Performance evaluation on real-world datasets, including human, viral, and bacterial samples, revealed ReadSeeker's high accuracy, exceeding 94%, with ROC-AUC scores above 98% in most cases.
Medical subject headings
- Software
- High-Throughput Nucleotide Sequencing
- Sequence Analysis, DNA
- Computational Biology