A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network
We propose a new alignment-free method for the classification of DNA barcoding based on both a spectral representation and prototype-based unsupervised clustering. We investigate how much the characteristics of different species are related to their DNA barcoding spectral distribution. We compare the proposed method with six state-of-the-art machine learning classifiers and the results confirm our method overcome all the other classifiers when applied to short fragments.
neural gas alignment-free analysis dna barcode classification k-mer representation