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...

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Detalles Bibliográficos
Autor principal: Daoud, Mosaab
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2020
Materias:
Research Communication
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
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author Daoud, Mosaab
author_facet Daoud, Mosaab
author_sort Daoud, Mosaab
collection PubMed
description 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 biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.
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spelling pubmed-71203452020-04-09 A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus Daoud, Mosaab Genomics Inform Research Communication 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 biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline. Korea Genome Organization 2020-03-31 /pmc/articles/PMC7120345/ /pubmed/32224840 http://dx.doi.org/10.5808/GI.2020.18.1.e7 Text en (c) 2020, Korea Genome Organization (CC) This is an open-access article distributed under the terms of the Creative Commons Attribution license(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Communication
Daoud, Mosaab
A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus
title A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus
title_full A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus
title_fullStr A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus
title_full_unstemmed A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus
title_short A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus
title_sort note on the distance distribution paradigm for mosaab-metric to process segmented genomes of influenza virus
topic Research Communication
url 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
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