Cargando…
Membrane Clustering of Coronavirus Variants Using Document Similarity
Currently, as an effect of the COVID-19 pandemic, bioinformatics, genomics, and biological computations are gaining increased attention. Genomes of viruses can be represented by character strings based on their nucleobases. Document similarity metrics can be applied to these strings to measure their...
Autores principales: | Lehotay-Kéry, Péter, Kiss, Attila |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689808/ https://www.ncbi.nlm.nih.gov/pubmed/36360202 http://dx.doi.org/10.3390/genes13111966 |
Ejemplares similares
-
A Novel Methodology for Measuring the Abstraction Capabilities of Image Recognition Algorithms
por: Hudáky, Márton Gyula, et al.
Publicado: (2021) -
An Efficient Parallelized Ontology Network-Based Semantic Similarity Measure for Big Biomedical Document Clustering
por: Li, Meijing, et al.
Publicado: (2021) -
Authorship identification of documents with high content similarity
por: Rexha, Andi, et al.
Publicado: (2018) -
Global evaluation of coronavirus disease 2019 cases and clustering of similar countries
por: Ankarali, Handan, et al.
Publicado: (2021) -
Adapting Document Similarity Measures for Ligand-Based Virtual Screening
por: Himmat, Mubarak, et al.
Publicado: (2016)