TY - JOUR
T1 - Taxonomic classification for living organisms using convolutional neural networks
AU - Khawaldeh, Saed
AU - Pervaiz, Usama
AU - Elsharnoby, Mohammed
AU - Alchalabi, Alaa Eddin
AU - Al-Zubi, Nayel
PY - 2017/11/17
Y1 - 2017/11/17
N2 - 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.
AB - 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.
KW - Convolutional neural networks
KW - DNA
KW - Encoding
KW - Genes
KW - Taxonomic classification
UR - http://www.scopus.com/inward/record.url?scp=85034773225&partnerID=8YFLogxK
U2 - 10.3390/genes8110326
DO - 10.3390/genes8110326
M3 - Article
AN - SCOPUS:85034773225
SN - 2073-4425
VL - 8
JO - Genes
JF - Genes
IS - 11
M1 - 326
ER -