Feature Selection for Genomic Signal Processing: Unsupervised, Supervised, and Self-Supervised Scenarios

Author:

Kung S. Y.,Luo Yuhui,Mak Man-Wai

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Modeling and Simulation,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering

Reference54 articles.

1. Guo, J., Mak, M. W., & Kung, S. Y. (2006). Eukaryotic protein subcellular localization based on local pairwise profile alignment SVM. In 2006 IEEE international workshop on machine learning for signal processing (MLSP’06) (pp. 391–396).

2. Reinhardt, A., & Hubbard, T. (1998). Using neural networks for prediction of the subcellular location of proteins. Nucleic Acids Research, 26, 2230–2236.

3. Pavlidis, P., Weston, J., Cai, J., & Grundy, W. N. (2001). Gene functional classification from heterogeneous data. In Int. conf. on computational biology (pp. 249–255). Pittsburgh: PA.

4. Leslie, C., ESKIN, E., & Noble, W. S. (2002). The spectrum kernel: A string kernel for SVM protein classification. In Altman, R. B., Dunker, A. K., Hunter, L., Lauredale, K., & Klein, T. E. (Eds.) Proc. of the pacific symposium on biocomputing. River Edge: World Scientific.

5. Leslie, C. S., Eskin, E., Cohen, A., Weston, J., & Noble, W. S. (2004). Mismatch string kernels for discriminative protein classification. Bioinformatics, 20(4), 467–476.

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