A protein acetylation prediction program 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.
Department of Pathology, School of Medicine, Yale University, New Haven, CT, USA; Laboratory of Cellular Dynamics, Hefei National Laboratory for Physical Sciences, and the University of Science and Technology of China, Hefei, China; College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China; Department of Physiology and Cancer Research Program, Morehouse School of Medicine, Atlanta, GA, USA