Predicting the protein SUMO modification sites based on Properties Sequential Forward Selection (PSFS)
Predicting the protein SUMO modification sites based on Properties Sequential Forward Selection (PSFS)
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DOI：
10.1016/j.bbrc.2007.04.097
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发表时间：
2007-06-22
影响因子：
3.1
通讯作者：
Cai, Yudong
中科院分区：
文献类型：
--
作者：
Liu, Boshu;Li, Sujun;Cai, Yudong
蛋白质相扑修饰是一种重要的翻译后修饰，预测方法的优化仍然是一个挑战。基于氨基酸索引数据库(http://www.genome.jp/aaindex).)收集的数百种氨基酸的序列正向选择，利用支持向量机算法，提出了一种新的相扑修饰位点预测方法我们的方法还与0/1系统进行了比较，在0/1系统中，20个氨基酸由20维向量(A=00000000000000000001，C=00000000000000000010等)表示。该方法的留一交叉验证总体准确率达到89.18%，高于0/1系统。这表明相扑修饰的预测过程与氨基酸的性质高度相关，为进一步研究相扑修饰和鉴定蛋白质中的相扑修饰位点提供了一个有用的工具。该软件在http://www.biosino.org/sumo.上有售(C)2007 Elsevier Inc.保留所有权利。
Protein SUMO modification is an important post-translational modification and the optimization of prediction methods remains a challenge. Here, by using Support Vector Machines algorithm (SVM), a novel computational method was developed for SUMO modification site prediction based on Sequential Forward Selection (SFS) of hundreds of amino acid properties, which are collected by Amino Acid Index database (http://www.genome.jp/aaindex). Our method also compares with the 0/1 system, in which the 20 amino acids are represented by 20-dimensional vectors (A = 00000000000000000001, C = 00000000000000000010 and so on). The overall accuracy of leave-one-out cross-validation for our method reaches 89.18%, which is higher than 0/1 system. It indicated that the SUMO modification prediction process is highly related to the amino acid property and this approach here provide a helpful toot for further investigation of the SUMO modification and identification of sumoylation sites in proteins. The software is available at http://www.biosino.org/sumo. (c) 2007 Elsevier Inc. All rights reserved.