A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

Journal: Artificial intelligence in medicine

Published Date: Jul 4, 2015

Abstract

OBJECTIVES: In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed.

Authors

Antonino Fiannaca

National Research Council of Italy, ICAR-CNR, via Ugo La Malfa 153, Palermo, 90146, Italy. fiannaca@pa.icar.cnr.it.
Massimo La Rosa

Institute of High-Performance Computing and Networking, National Research Council of Italy, Viale delle Scienze, Ed. 11, 90128 Palermo, Italy.
Riccardo Rizzo

National Research Council of Italy, ICAR-CNR, via Ugo La Malfa 153, Palermo, 90146, Italy.
Alfonso Urso

Istituto di Calcolo e Reti ad Alte Prestazioni-Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy.

Keywords

Algorithms Animals Base Sequence Cluster Analysis Computational Biology Databases, Genetic Decision Trees DNA DNA Barcoding, Taxonomic Neural Networks, Computer Reproducibility of Results Species Specificity Supervised Machine Learning Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (26170017)

A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

Abstract

Authors

Keywords

External Resources

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