Abstract
In this paper we present an application of the neural gas network to the classification of the DNA barcode sequences. The proposed method is based on the identification of distinctive words, extracted from the spectral representation of DNA sequences. In particular we calculated the “signatures” that are a characteristic of the DNA sequence at different taxonomic levels. In order to demonstrate the efficacy of the proposed method, we tested it over 10 real barcode datasets belonging to different animalia species, provided by on-line resource Barcode of Life Database (BOLD).
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Fiannaca, A., La Rosa, M., Rizzo, R., Urso, A. (2013). Analysis of DNA Barcode Sequences Using Neural Gas and Spectral Representation. In: Iliadis, L., Papadopoulos, H., Jayne, C. (eds) Engineering Applications of Neural Networks. EANN 2013. Communications in Computer and Information Science, vol 384. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41016-1_23
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DOI: https://doi.org/10.1007/978-3-642-41016-1_23
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