PREDICTING SUBCELLULAR LOCATION OF APOPTOSIS PROTEINS USING THE ALGORITHM OF THE INCREMENT OF DIVERSITY COMBINED WITH SUPPORT VECTOR MACHINES
基于离散增量结合支持向量机方法的凋亡蛋白亚细胞位置预测

According to the concept that the subcellular location of an apoptosis protein is mainly determined by its amino acid sequence,the six kind of subcellular locations of apoptosis proteins were predicted by using the algorithm of the increment of diversity(ID) combined with support vector machines(ID_SVM) based on the n-peptide components of local amino acid sequence and hydropathy and hydrophobicity.The results of Re-substitution and Jackknife tests showed that total predictive success rates for ID_SVM algorithm were 94.6% and 84.2%,respectively.The results of 5-fold cross-validation(5-CV) and 10-fold cross-validation(10-CV) tests showed that total predictive success rates were higher than 83%.By comparing the predicted ability of ID with ID_SVM,the authors found that the predictive success rate could be improved by combining ID-model with support vector machines.These results indicate that the ID_SVM algorithm is an effective method for predicting the subcellular location of apoptosis proteins.