| Literature DB >> 28682641 |
Haixin Ai1,2, Runlin Wu3, Li Zhang1,2, Xuewei Wu1, Junchao Ma3, Huan Hu1, Liangchao Huang3, Wen Chen3, Jian Zhao1, Hongsheng Liu1,2.
Abstract
Lysine succinylation is an extremely important protein post-translational modification that plays a fundamental role in regulating various biological reactions, and dysfunction of this process is associated with a number of diseases. Thus, determining which Lys residues in an uncharacterized protein sequence are succinylated underpins both basic research and drug development endeavors. To solve this problem, we have developed a predictor called pSuc-PseRat. The features of the pSuc-PseRat predictor are derived from two aspects: (1) the binary encoding from succinylated sites and non-succinylated sites; (2) the sequence-coupling effects between succinylated sites and non-succinylated sites. Eleven gradient boosting machine classifiers were trained with these features to build the predictor. The pSuc-PseRat predictor achieved an average ACU (area under the receiver operating characteristic curve) score of 0.805 in the fivefold cross-validation set and performed better than existing predictors on two comprehensive independent test sets. A freely available web server has been developed for pSuc-PseRat.Entities:
Keywords: binary encoding; gradient boosting machine; lysine succinylation.
Mesh:
Substances:
Year: 2017 PMID: 28682641 DOI: 10.1089/cmb.2016.0206
Source DB: PubMed Journal: J Comput Biol ISSN: 1066-5277 Impact factor: 1.479