Title
GenFooT: Genomic Footprint of mitochondrial sequence for Taxonomy classification
Abstract
The annotation of the sequences plays an important role in the taxonomic characteristics, medical research, phylogenetic studies, etc. Most of the existing classification techniques focused on some distinct group of organisms and considered the specific fragments of genome sequence, such as particular gene or RNAs. Here, we introduce a novel representation of genome sequence in a 2D coordinate space and extract features from the 2D representation. These features are used to classify a set of species into different taxonomy ranks. We experiment our proposed method, GenFooT, on nine different datasets of genomic sequences of various organisms. Our experimental results indicate improved classification performance of the proposed features with both Linear discriminant analysis and Logistic regression classifiers. This study demonstrates that our proposed alignment-free method, GenFooT, is fast, accurate, and can be applied to the large-scale genomics studies.
Year
DOI
Venue
2020
10.1109/BIBM49941.2020.9313475
2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Keywords
DocType
ISBN
taxonomy classification,mitochondrial genome,Genomic Footprint
Conference
978-1-7281-6216-4
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Aritra Mahapatra100.34
Jayanta Mukherjee237856.06