Journal of Biomedical Science and Engineering

Vol.8 No.10(2015), Paper ID 60283, 11 pages

DOI:10.4236/jbise.2015.810065

 

Sequence Motif-Based One-Class Classifiers Can Achieve Comparable Accuracy to Two-Class Learners for Plant microRNA Detection

 

Malik Yousef, Jens Allmer, Waleed Khalifa

 

The Institute of Applied Research, The Galilee Society, Shefa Amr, Israel
Molecular Biology and Genetics, Izmir Institute of Technology, Izmir, Turkey
Computer Science, The College of Sakhnin, Sakhnin, Israel
Bionia Incorporated, IZTEKGEB A8, Izmir, Turkey

 

Copyright © 2015 Malik Yousef, Jens Allmer, Waleed Khalifa 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.

 

How to Cite this Article


Yousef, M. , Allmer, J. and Khalifa, W. (2015) Sequence Motif-Based One-Class Classifiers Can Achieve Comparable Accuracy to Two-Class Learners for Plant microRNA Detection. Journal of Biomedical Science and Engineering, 8, 684-694. doi: 10.4236/jbise.2015.810065.

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