A mapping-free natural language processing-based technique for sequence search in nanopore long-reads
We conclude that for long Oxford nanopore reads, a natural language processing-based approach can reliably replace classical mapping when there is a need for fast, reliable and energy and computationally efficient targeted mapping of a pre-defined subset of transcripts. The developed model can be easily retrained to identify selected transcripts and/or work with various long-read sequencing techniques. Our results of the study clearly demonstrate the potential of applying techniques known from classical text processing to nucleotide sequences.
Authors
- Christophe Badie (ORCID: https://orcid.org/0000-0003-4572-5008)
- Joanna Polańska (ORCID: https://orcid.org/0000-0001-8004-9864)
- Mustafa A. Najim (ORCID: https://orcid.org/0000-0003-2884-3731)
- Lourdes Cruz-Garcia (ORCID: https://orcid.org/0000-0002-7804-974X)
- Tomasz Strzoda
Institutions
- Silesian University of Technology (PL)
- UK Health Security Agency (GB)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2024-11-13
- DOI
- https://doi.org/10.1186/s12859-024-05980-7
- Citations
- 1
- Primary Topic
- Nanopore and Nanochannel Transport Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.18
Funders
- Silesian University of Technology