ArticleGenomics & informatics2019
Insights of Window-Based Mechanism Approach to Visualize Composite BioData Point in Feature Spaces.
Article in Genomics & informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Detecting outliers in segmented genomes of flu virus using an alignment-free approach.Genomics & informatics · 2020Article
- A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus.Genomics & informatics · 2020Article
- The extension of the largest generalized-eigenvalue based distance metric D_ij (γ_1 ) in arbitrary feature spaces to classify composite data points.Genomics & informatics · 2019Article
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Authors and funding
1 author.
Funding
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Abstract
In this paper, we propose a window-based mechanism visualization approach as an alternative way to measure the seriousness of the difference among data-insights extracted from a composite biodata point. The approach is based on two components: undirected graph and Mosaab-metric space. The significant application of this approach is to visualize the segmented genome of a virus. We use Influenza and Ebola viruses as examples to demonstrate the robustness of this approach and to conduct comparisons. This approach can provide researchers with deep insights about information structures extracted from a segmented genome as a composite biodata point, and consequently, to capture the segmented genetic variations and diversity (variants) in composite data points.
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