Identifying RNA-protein interactions using feature dimension reduction method

In this paper, a new system is proposed to improve the performance of protein-RNA interaction prediction. First of all, the protein sequences are quantized into a high dimension space using an effective sequence encoding scheme. However, the problem caused by such representation is small sample size problem, where the data dimension is much larger than the sample size. To sort out this problem, a new dimension reduction algorithm is introduced. It extracts the essential features from the high dimension feature space and does not suffer from small sample size problem. Then, an efficient classifier is employed to recognize the protein-RNA interaction according to the new features after dimension reduction.