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Iqbal, M.J., Faye, I., Samir, B.B. and Said, A.M. (2014) Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics. The Scientific World Journal, 2014, Article ID: 173869.

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.