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Sci Rep. 2015 Jun 18;5:10184. doi: 10.1038/srep10184.

iSuc-PseAAC: predicting lysine succinylation in proteins by incorporating peptide position-specific propensity.

Author information

1
Department of Information and Computer Science, University of Science and Technology Beijing, Beijing 100083, China.
2
Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.
3
College of Science, China Agricultural University, Beijing 100083, China.

Abstract

Lysine succinylation in protein is one type of post-translational modifications (PTMs). Succinylation is associated with some diseases and succinylated sites data just has been found in recent years in experiments. It is highly desired to develop computational methods to identify the candidate proteins and their sites. In view of this, a new predictor called iSuc-PseAAC was proposed by incorporating the peptide position-specific propensity into the general form of pseudo amino acid composition. The accuracy is 79.94%, sensitivity 51.07%, specificity 89.42% and MCC 0.431 in leave-one-out cross validation with support vector machine algorithm. It demonstrated by rigorous leave-one-out on stringent benchmark dataset that the new predictor is quite promising and may become a useful high throughput tool in this area. Meanwhile a user-friendly web-server for iSuc-PseAAC is accessible at http://app.aporc.org/iSuc-PseAAC/. Users can easily obtain their desired results without the need to understand the complicated mathematical equations presented in this paper just for its integrity.

PMID:
26084794
PMCID:
PMC4471726
DOI:
10.1038/srep10184
[Indexed for MEDLINE]
Free PMC Article

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