Author(s)

Dau Phan¹, Ngoc Giang Nguyen¹, Favorisen Rosyking Lumbanraja¹, Mohammad Reza Faisal¹, Bahriddin Abapihi¹, Bedy Purnama¹, Mera Kartika Delimayanti¹, Mamoru Kubo², Kenji Satou²

¹Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa, Japan.
²Institute of Science and Engineering, Kanazawa University, Kanazawa, Japan.

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.

Sequence Classification, Numerical and Categorical Features, Feature Selection

Phan, D. , Nguyen, N. , Lumbanraja, F. , Faisal, M. , Abapihi, B. , Purnama, B. , Delimayanti, M. , Kubo, M. and Satou, K. (2017) Combined Use of k-Mer Numerical Features and Position-Specific Categorical Features in Fixed-Length DNA Sequence Classification. Journal of Biomedical Science and Engineering, 10, 390-401. doi: 10.4236/jbise.2017.108030.