Summary
International Technical Conference on Circuits/Systems, Computers and Communications
2008
Session Number:C1
Session:
Number:C1-4
Evaluation of N-myristoylation Prediction Tool using Machine Learning
Sayaka Kado, Ryo Okada, Manabu Sugii, Hiroshi Matsuno, Satoru Miyano,
pp.-
Publication Date:2008/7/7
Online ISSN:2188-5079
Summary:
Protein sequences constitute molecular complex in an organism. However it is difficult to find a sequence rule such as cascade reaction signals, post translational modification signals and so on.These sequence signals perform an essential role in regulating cellular structure and function. In previous study, we could find sequence rules of N-myristoylated proteins easily with computational approach. Subsequently, we have developed a CGI tool to predict N-myristoylated proteins with their sequence rules. In this study, we performed accuracy evaluation of our developed CGI tool. As a result, we show that developed CGI tool predict N-myristoylated proteins effectively with characteristics of N-myristoylated protein sequences.