A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus

Abstract

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.

Keywords

• composite data point
• distance distribution paradigm
• mosaab-metric space
• segmented genome of influenza virus