A web tool for predicting the protein Acetylation site based on support vector machine (SVM), which is training depend on the amino acid sequence and other structural characteristics, such as accessible surface area, absolute entropy, non-bonded energy, size, amino acid composition, steric parameter, hydrophobicity, volume, mean polarity, electric charge, heat capacity and isoelectric point which is surrounding the modification site and implemented two stages SVM method. N-Ace not only provides a user-friendly input/output interface but also is a creative method for predicting protein acetylation sites.
Department of Computer Science and Engineering, Yuan Ze University, Taiwan; Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Taiwan; Institute of Tropical Plant Sciences, National Cheng Kung University, Taiwan; Institute of Molecular Medicine and Bioengineering, National Chiao Tung University, Taiwan; Department of Biological Science and Technology, National Chiao Tung University, Taiwan
N-Ace funding source(s)
National Science Council of the Republic of China, Taiwan (Grant Numbers: NSC 98-2627-B-009-005, NSC 98-2311-B-009-004-MY3, NSC 99-2320-B-155-001)