LipoSVM: Prediction of Lysine Lipoylation in Proteins based on the Support Vector Machine.

ABSTRACT:

Background

Lysine lipoylation which is a rare and highly conserved post-translational modification of proteins has been considered as one of the most important processes in the biological field. To obtain a comprehensive understanding of regulatory mechanism of lysine lipoylation, the key is to identify lysine lipoylated sites. The experimental methods are expensive and laborious. Due to the high cost and complexity of experimental methods, it is urgent to develop computational ways to predict lipoylation sites.

Methodology

In this work, a predictor named LipoSVM is developed to accurately predict lipoylation sites. To overcome the problem of an unbalanced sample, synthetic minority over-sampling technique (SMOTE) is utilized to balance negative and positive samples. Further

SUBMITTER: Wu M 

PROVIDER: S-EPMC7235397 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature