Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection.

ABSTRACT: Lysine malonylation is an important post-translational modification (PTM) in proteins, and has been characterized to be associated with diseases. However, identifying malonyllysine sites still remains to be a great challenge due to the labor-intensive and time-consuming experiments. In view of this situation, the establishment of a useful computational method and the development of an efficient predictor are highly desired. In this study, a predictor Mal-Lys which incorporated residue sequence order information, position-specific amino acid propensity and physicochemical properties was proposed. A feature selection method of minimum Redundancy Maximum Relevance (mRMR) was used to select optimal ones from the whole features. With the leave-one-out validation, the value of the area under the

SUBMITTER: Xu Y 

PROVIDER: S-EPMC5133563 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature