Detecting outliers in segmented genomes of flu virus using an alignment-free approach
In this paper, we propose a new approach to detecting outliers in a set of segmented genomes of the flu virus, a data set with a heterogeneous set of sequences. The approach has the following computational phases: feature extraction, which is a mapping into feature space, alignment-free distance mea...
Main Author: | Mosaab Daoud |
---|---|
Format: | Article |
Language: | English |
Published: |
Korea Genome Organization
2020-03-01
|
Series: | Genomics & Informatics |
Subjects: | |
Online Access: | http://genominfo.org/upload/pdf/gi-2020-18-1-e2.pdf |
Similar Items
-
A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus
by: Mosaab Daoud
Published: (2020-03-01) -
Insights of window-bsed mechanism approach to visualize composite bioData point in feature spaces
by: Mosaab Daoud
Published: (2019-03-01) -
Detection of Outliers in Univariate Circular Data by Means of the Outlier Local Factor (LOF)
by: Ali H. Abuzaid
Published: (2020-09-01) -
Exploring Ways of Identifying Outliers in Spatial Point Patterns
by: Liu, Jie
Published: (2015) -
Outliers and Regression Models
by: Mitchell, Napoleon
Published: (1992)