Prediction of S-Nitrosylation Modification Sites Based on Kernel Sparse Representation Classification and mRMR Algorithm

Algorithm 2

SRC algorithm.

Input: the training set with distinct classes, the test sample

Output: the category of the testing sample

(1) Concatenate all training samples to construct the matrix

(2) normalize columns of the matrix with the norm

(3) solve (7) or (8) using the OMP in Algorithm 1, and obtain the coefficient vector

(4) determine the category of the testing sample according to (9)