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Taxonomic Classification for Living Organisms Using Convolutional Neural Networks

Taxonomic classification has a wide-range of applications such as finding out more about evolutionary history. Compared to the estimated number of organisms that nature harbors, humanity does not have a thorough comprehension of to which specific classes they belong. The classification of living organisms can be done in many machine learning techniques. However, in this study, this is performed using convolutional neural networks. Moreover, a DNA encoding technique is incorporated in the algorithm to increase performance and avoid misclassifications. The algorithm proposed outperformed the state of the art algorithms in terms of accuracy and sensitivity, which illustrates a high potential for using it in many other applications in genome analysis

Genes, 2017, vol. 8, n煤m. 11, p. 326-337

MDPI (Multidisciplinary Digital Publishing Institute)

Author: Khawaldeh, Saed
Pervaiz, Usama
Elsharnoby, Mohammed
Alchalabi, Alaa Eddin
Al-Zubi, Nayel
Date: 2017 November 17
Abstract: Taxonomic classification has a wide-range of applications such as finding out more about evolutionary history. Compared to the estimated number of organisms that nature harbors, humanity does not have a thorough comprehension of to which specific classes they belong. The classification of living organisms can be done in many machine learning techniques. However, in this study, this is performed using convolutional neural networks. Moreover, a DNA encoding technique is incorporated in the algorithm to increase performance and avoid misclassifications. The algorithm proposed outperformed the state of the art algorithms in terms of accuracy and sensitivity, which illustrates a high potential for using it in many other applications in genome analysis
Format: application/pdf
Citation: https://doi.org/10.3390/genes8110326
ISSN: 2073-4425
Document access: http://hdl.handle.net/10256/14736
Language: eng
Publisher: MDPI (Multidisciplinary Digital Publishing Institute)
Collection: Reproducci贸 digital del document publicat a: https://doi.org/10.3390/genes8110326
Articles publicats (D-ATC)
Is part of: Genes, 2017, vol. 8, n煤m. 11, p. 326-337
Rights: Attribution 3.0 Spain
Rights URI: http://creativecommons.org/licenses/by/3.0/es/
Subject: ADN
DNA
Gens
Genes
Biologia -- Classificaci贸
Biology -- Classification
Codificaci贸, Teoria de la
Coding theory
Title: Taxonomic Classification for Living Organisms Using Convolutional Neural Networks
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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