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Advances in Bioinformatics
Volume 2016, Article ID 5670851, 6 pages
http://dx.doi.org/10.1155/2016/5670851
Research Article

Feature Selection Has a Large Impact on One-Class Classification Accuracy for MicroRNAs in Plants

1Computer Science, The College of Sakhnin, 30810 Sakhnin, Israel
2The Institute of Applied Research, The Galilee Society, P.O. Box 437, 20200 Shefa Amr, Israel
3Molecular Biology and Genetics, Izmir Institute of Technology, Urla, 35430 Izmir, Turkey
4Bionia Incorporated, IZTEKGEB A8, Urla, 35430 Izmir, Turkey

Received 31 October 2015; Accepted 16 March 2016

Academic Editor: Paul Harrison

Copyright © 2016 Malik Yousef et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [6 citations]

The following is the list of published articles that have cited the current article.

  • Waleed Khalifa, Malik Yousef, Müşerref Duygu Saçar Demirci, and Jens Allmer, “The impact of feature selection on one and two-class classification performance for plant microRNAs,” PeerJ, vol. 4, pp. e2135, 2016. View at Publisher · View at Google Scholar
  • Firuz Kamalov, and Fadi Thabtah, “A Feature Selection Method Based on Ranked Vector Scores of Features for Classification,” Annals of Data Science, 2017. View at Publisher · View at Google Scholar
  • Ahmed A. Ewees, Mohamed Abd El Aziz, and Aboul Ella Hassanien, “Chaotic multi-verse optimizer-based feature selection,” Neural Computing and Applications, 2017. View at Publisher · View at Google Scholar
  • Müşerref Duygu Saçar Demirci, and Jens Allmer, “Delineating the impact of machine learning elements in pre-microRNA detection,” PeerJ, vol. 5, pp. e3131, 2017. View at Publisher · View at Google Scholar
  • Luis Trejo, and Ari Barrera-Animas, “Towards an Efficient One-Class Classifier for Mobile Devices and Wearable Sensors on the Context of Personal Risk Detection,” Sensors, vol. 18, no. 9, pp. 2857, 2018. View at Publisher · View at Google Scholar
  • Malik Yousef, “Hamming Distance and K-mer Features for Classification of Pre-cursor microRNAs from Different Species,” Proceedings of the 1st International Conference on Smart Innovation, Ergonomics and Applied Human Factors (SEAHF), vol. 150, pp. 180–189, 2019. View at Publisher · View at Google Scholar