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Gene. 2016 Jan 15;576(1 Pt 1):99-104. doi: 10.1016/j.gene.2015.09.072. Epub 2015 Nov 9.

Prediction of sumoylation sites in proteins using linear discriminant analysis.

Author information

1
Department of Information and Computer Science, University of Science and Technology Beijing, Beijing 100083, China.
2
College of Science, China Agricultural University, Beijing 100083, China.
3
School of Statistics, Capital University of Economics and Business, Beijing, 100070, China. Electronic address: llm5609@163.com.

Abstract

Sumoylation is a multifunctional post-translation modification (PTM) in proteins by the small ubiquitin-related modifiers (SUMOs), which have relations to ubiquitin in molecular structure. Sumoylation has been found to be involved in some cellular processes. It is very significant to identify the exact sumoylation sites in proteins for not only basic researches but also drug developments. Comparing with time exhausting experiment methods, it is highly desired to develop computational methods for prediction of sumoylation sites as a complement to experiment in the post-genomic age. In this work, three feature constructions (AAIndex, position-specific amino acid propensity and modification of composition of k-space amino acid pairs) and five different combinations of them were used to construct features. At last, 178 features were selected as the optimal features according to the Mathew's correlation coefficient values in 10-fold cross validation based on linear discriminant analysis. In 10-fold cross-validation on the benchmark dataset, the accuracy and Mathew's correlation coefficient were 86.92% and 0.6845. Comparing with those existing predictors, SUMO_LDA showed its better performance.

KEYWORDS:

F-score; Post-translational modification; Pseudo amino acid

PMID:
26432000
DOI:
10.1016/j.gene.2015.09.072
[Indexed for MEDLINE]

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