iSucc-PseAAC:Prediction of Lysine Succinylation Modification Sites Based on Ensemble Machine Learning / 中国生物化学与分子生物学报

ABSTRACT

Lysine succinylation is a novel post-translational modification, which plays an important role in regulating distinct cellular functions control, therefore it is necessary to accurately identify succinylation sites in proteins. As traditional experiments consume material and financial resources, prediction by calculation is an efficient method being proposed recently. In this study, we developed a new prediction method iSucc-PseAAC, which uses a variety of classification algorithms combined with different feature extraction methods. Moreover, it is found that under the feature extraction based on coupled sequence (PseAAC), the classification effect of support vector machine is the best, and it could be combined with ensemble learning to solve the problem of data imbalance. Compared with the existing methods, iSucc-PseAAC has more significance and practicality in predicting lysine succinylation sites.