fiee 16(9): e4

Research Article

Species Identification Using Part of DNA Sequence: Evidence from Machine Learning Algorithms

Download1198 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eai.3-12-2015.2262476,
    author={Taha Alhersh and Brahim Belhaouari Samir and Hamada Al-Absi and Abdullah Alorainy and Belloui Bouzid},
    title={Species Identification Using Part of DNA Sequence: Evidence from Machine Learning Algorithms},
    journal={EAI Endorsed Transactions on Future Intelligent Educational Environments},
    volume={2},
    number={9},
    publisher={ACM},
    journal_a={FIEE},
    year={2016},
    month={5},
    keywords={machine learning, species identification, dna sequences, feature selection},
    doi={10.4108/eai.3-12-2015.2262476}
}
  • Taha Alhersh
    Brahim Belhaouari Samir
    Hamada Al-Absi
    Abdullah Alorainy
    Belloui Bouzid
    Year: 2016
    Species Identification Using Part of DNA Sequence: Evidence from Machine Learning Algorithms
    FIEE
    EAI
    DOI: 10.4108/eai.3-12-2015.2262476
Taha Alhersh1,*, Brahim Belhaouari Samir2, Hamada Al-Absi3, Abdullah Alorainy4, Belloui Bouzid5
  • 1: Telemedicine Multidisciplinary Research Platform Monash University Malaysia
  • 2: Department of Mathematics Sharjah University
  • 3: Faculty of Engineering, Computing and Science Swinburne University of Technology Sarawak Campus
  • 4: King Abdulaziz City for Science and Technology
  • 5: University of Hafr Al Batin
*Contact email: taha.trh@gmail.com

Abstract

In biological studies, species identification is considered one of the most important issues. Several methods have been suggested to identify species using the whole DNA sequences. In this study, we present new insights for species identification using only part of the DNA sequence. The Clustering k-Nearest Neighbor (K-C-NN) and Support Vector Machine (SVM) classifiers were used to test and evaluate the improved statistical features extracted from DNA sequences for four species (Aquifex aeolicus, Bacillus subtilis, Aeropyrum pernix and Buchnera sp). The results show that part of DNA sequences can be used to identify species.

Keywords
machine learning, species identification, dna sequences, feature selection
Published
2016-05-24
Publisher
ACM
http://dx.doi.org/10.4108/eai.3-12-2015.2262476

Copyright © 2015 T. Alhersh et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.