Cargando…
A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus
In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and b...
Autor principal: | Daoud, Mosaab |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korea Genome Organization
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120345/ https://www.ncbi.nlm.nih.gov/pubmed/32224840 http://dx.doi.org/10.5808/GI.2020.18.1.e7 |
Ejemplares similares
-
The extension of the largest generalized-eigenvalue based distance metric D(ij)(γ(1)) in arbitrary feature spaces to classify composite data points
por: Daoud, Mosaab
Publicado: (2019) -
Detecting outliers in segmented genomes of flu virus using an alignment-free approach
por: Daoud, Mosaab
Publicado: (2020) -
Adaptive Distance Metric Learning for Diffusion Tensor Image Segmentation
por: Kong, Youyong, et al.
Publicado: (2014) -
Insights of window-bsed mechanism approach to visualize composite bioData point in feature spaces
por: Daoud, Mosaab
Publicado: (2019) -
Theoretical properties of distance distributions and novel metrics for nearest-neighbor feature selection
por: Dawkins, Bryan A., et al.
Publicado: (2021)