Format

Send to

Choose Destination
Biochem Biophys Res Commun. 2006 Dec 1;350(4):818-24. Epub 2006 Oct 2.

Prediction of Nepsilon-acetylation on internal lysines implemented in Bayesian Discriminant Method.

Author information

1
Department of Pathology, School of Medicine, Yale University, New Haven, CT 06520, USA.

Abstract

Protein acetylation is an important and reversible post-translational modification (PTM), and it governs a variety of cellular dynamics and plasticity. Experimental identification of acetylation sites is labor-intensive and often limited by the availability of reagents such as acetyl-specific antibodies and optimization of enzymatic reactions. Computational analyses may facilitate the identification of potential acetylation sites and provide insights into further experimentation. In this manuscript, we present a novel protein acetylation prediction program named PAIL, prediction of acetylation on internal lysines, implemented in a BDM (Bayesian Discriminant Method) algorithm. The accuracies of PAIL are 85.13%, 87.97%, and 89.21% at low, medium, and high thresholds, respectively. Both Jack-Knife validation and n-fold cross-validation have been performed to show that PAIL is accurate and robust. Taken together, we propose that PAIL is a novel predictor for identification of protein acetylation sites and may serve as an important tool to study the function of protein acetylation. PAIL has been implemented in PHP and is freely available on a web server at: http://bioinformatics.lcd-ustc.org/pail.

PMID:
17045240
PMCID:
PMC2093955
DOI:
10.1016/j.bbrc.2006.08.199
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center