GRaphical Footprint Based Alignment-Free Method (GRAFree) for Classifying the Species in Large-Scale Genomics
In our study, we propose to use novel features from mitochondrial genomic sequences reflecting their evolutionary traits by a novel GRaphical footprint based Alignment-Free method (GRAFree). These features are used to classify a set of species to different classes. A novel distance measure in the feature space is also proposed to measure the proximity of these species in the evolutionary processes. The distance function is found to be a metric. Further we model the evolutionary relationships of these classes by forming a phylogenetic tree. Experimentations were carried out with 157 species covering four different classes such as, Insecta, Actinopterygii, Aves, and Mammalia. We apply our proposed distance function on the selected feature vectors for three different graphical representations of genome. The inferred trees corroborate accepted evolutionary traits. This demonstrates that our proposed distance function and feature representation can be applied to classify different species and to capture the evolutionary relationships among their classes.
KeywordsClassification Phylogeny Mitochondrial genome Graphical footprint k-nearest neighbor classifier Hierarchical clustering
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