Identification of antioxidants from sequence information using naïve Bayes.
Identification of antioxidants from sequence information using naïve Bayes.
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DOI：
10.1155/2013/567529
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发表时间：
2013
影响因子：
--
通讯作者：
Chen W
中科院分区：
文献类型：
--
作者：
Feng PM;Lin H;Chen W
抗氧化蛋白是保护细胞免受自由基损害的物质。准确鉴定新的抗氧化蛋白对于了解它们在延缓衰老中的作用非常重要。因此，它是非常可取的，以发展计算方法来识别抗氧化蛋白。本文提出了一种基于朴素贝叶斯的抗氧化蛋白预测方法，利用氨基酸组成和二肽组成预测抗氧化蛋白。为了去除冗余信息，采用了一种新的特征选择技术来挑选出优化的特征。在刀切测试中，该方法实现了66.88%的准确率之间的抗氧化剂和非抗氧化剂蛋白质的区别，这是上级的其他国家的最先进的分类器。这些结果表明，该方法可能是一种有效的和有前途的高通量抗氧化蛋白鉴定方法。
Antioxidant proteins are substances that protect cells from the damage caused by free radicals. Accurate identification of new antioxidant proteins is important in understanding their roles in delaying aging. Therefore, it is highly desirable to develop computational methods to identify antioxidant proteins. In this study, a Naïve Bayes-based method was proposed to predict antioxidant proteins using amino acid compositions and dipeptide compositions. In order to remove redundant information, a novel feature selection technique was employed to single out optimized features. In the jackknife test, the proposed method achieved an accuracy of 66.88% for the discrimination between antioxidant and nonantioxidant proteins, which is superior to that of other state-of-the-art classifiers. These results suggest that the proposed method could be an effective and promising high-throughput method for antioxidant protein identification.