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BMC Bioinformatics. 2006 Oct 17;7:458.

NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm.

Author information

1
Laboratory of Cellular Dynamics, Hefei National Laboratory for Physical Sciences, and the University of Science and Technology of China, Hefei, China. yxue@mail.ustc.edu.cn

Abstract

BACKGROUND:

Protein palmitoylation, an essential and reversible post-translational modification (PTM), has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design.

RESULTS:

In this work, we present NBA-Palm, a novel computational method based on Naïve Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed) and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation. Two more algorithms, RBF network and support vector machine (SVM), also have been employed and compared with NBA-Palm.

CONCLUSION:

Taken together, our analyses demonstrate that NBA-Palm is a useful computational program that provides insights for further experimentation. The accuracy of NBA-Palm is comparable with our previously described tool CSS-Palm. The NBA-Palm is freely accessible from: http://www.bioinfo.tsinghua.edu.cn/NBA-Palm.

PMID:
17044919
PMCID:
PMC1624852
DOI:
10.1186/1471-2105-7-458
[Indexed for MEDLINE]
Free PMC Article

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