PRCFX-DT: a new graph-based approach for feature selection and classification of genomic sequences
The proposed algorithm was successfully tested on several types of viruses, and the interpretability of the extracted features also enabled its structural analysis. The use of a graph-based approach on genetic features containing information about the internal structure of nucleotides yielded results that could be significant for the identification of any type of virus or specific viral variant.
Authors
- Sania Eskandari (ORCID: https://orcid.org/0000-0002-6347-2596)
- Hadi Sharifi (ORCID: https://orcid.org/0000-0002-4852-540X)
- Amin Khodaei (ORCID: https://orcid.org/0000-0002-8175-5039)
- Behzad Mozaffari Tazehkand (ORCID: https://orcid.org/0000-0002-0734-5816)
Institutions
- University of Kentucky (US)
- University of Tabriz (IR)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1186/s12859-025-06183-4
- Citations
- 3
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 2.42