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IHEC_RAAC: a online platform for identifying human enzyme classes via reduced amino acid cluster strategy
Amino Acids ( IF 3.5 ) Pub Date : 2021-01-23 , DOI: 10.1007/s00726-021-02941-9
Hao Wang 1 , Qilemuge Xi 1 , Pengfei Liang 1 , Lei Zheng 1 , Yan Hong 1 , Yongchun Zuo 1
Affiliation  

Enzymes have been proven to play considerable roles in disease diagnosis and biological functions. The feature extraction that truly reflects the intrinsic properties of protein is the most critical step for the automatic identification of enzymes. Although lots of feature extraction methods have been proposed, some challenges remain. In this study, we developed a predictor called IHEC_RAAC, which has the capability to identify whether a protein is a human enzyme and distinguish the function of the human enzyme. To improve the feature representation ability, protein sequences were encoded by a new feature-vector called ‘reduced amino acid cluster’. We calculated 673 amino acid reduction alphabets to determine the optimal feature representative scheme. The tenfold cross-validation test showed that the accuracy of IHEC_RAAC to identify human enzymes was 74.66% and further discriminate the human enzyme classes with an accuracy of 54.78%, which was 2.06% and 8.68% higher than the state-of-the-art predictors, respectively. Additionally, the results from the independent dataset indicated that IHEC_RAAC can effectively predict human enzymes and human enzyme classes to further provide guidance for protein research. A user-friendly web server, IHEC_RAAC, is freely accessible at http://bioinfor.imu.edu.cn/ihecraac.



中文翻译:

IHEC_RAAC:通过减少氨基酸簇策略识别人类酶类的在线平台

酶已被证明在疾病诊断和生物学功能中发挥着重要作用。真正反映蛋白质内在特性的特征提取是酶类自动识别最关键的一步。尽管已经提出了许多特征提取方法,但仍然存在一些挑战。在这项研究中,我们开发了一个名为 IHEC_RAAC 的预测器,它能够识别蛋白质是否是人类酶并区分人类酶的功能。为了提高特征表示能力,蛋白质序列由一种称为“减少氨基酸簇”的新特征向量编码。我们计算了 673 个氨基酸减少字母表以确定最佳特征代表方案。十倍交叉验证测试表明,IHEC_RAAC识别人类酶的准确率为74.66%,进一步区分人类酶类别的准确率为54.78%,分别比最先进的2.06%和8.68%分别为预测因子。此外,来自独立数据集的结果表明,IHEC_RAAC 可以有效预测人类酶和人类酶的类别,为进一步为蛋白质研究提供指导。用户友好的 Web 服务器 IHEC_RAAC 可在 http://bioinfor.imu.edu.cn/ihecraac 上免费访问。来自独立数据集的结果表明,IHEC_RAAC 可以有效预测人类酶和人类酶类别,为进一步为蛋白质研究提供指导。用户友好的 Web 服务器 IHEC_RAAC 可在 http://bioinfor.imu.edu.cn/ihecraac 上免费访问。来自独立数据集的结果表明,IHEC_RAAC 可以有效预测人类酶和人类酶类别,为进一步为蛋白质研究提供指导。用户友好的 Web 服务器 IHEC_RAAC 可在 http://bioinfor.imu.edu.cn/ihecraac 上免费访问。

更新日期:2021-01-24
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