Nguyen, N.G., Tran, V.A., Ngo, D.L., Phan, D., Lumbanraja, F.R., Faisal, M.R., Abapihi, B., Kubo, M. and Satou, K. (2016) DNA Sequence Classification by Convolutional Neural Network. Journal of Biomedical Science and Engineering, 9, 280-286.
https://doi.org/10.4236/jbise.2016.95021

has been cited by the following article:

• TITLE: Combined Use of k-Mer Numerical Features and Position-Specific Categorical Features in Fixed-Length DNA Sequence Classification

  AUTHORS: Dau Phan, Ngoc Giang Nguyen, Favorisen Rosyking Lumbanraja, Mohammad Reza Faisal, Bahriddin Abapihi, Bedy Purnama, Mera Kartika Delimayanti, Mamoru Kubo, Kenji Satou

  KEYWORDS: Sequence Classification, Numerical and Categorical Features, Feature Selection

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.10 No.8, August 30, 2017

  ABSTRACT: To classify DNA sequences, k-mer frequency is widely used since it can convert variable-length sequences into fixed-length and numerical feature vectors. However, in case of fixed-length DNA sequence classification, subsequences starting at a specific position of the given sequence can also be used as categorical features. Through the performance evaluation on six datasets of fixed-length DNA sequences, our algorithm based on the above idea achieved comparable or better performance than other state-of-the art algorithms.