Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Center for Genomics and Computational Biology, School of Life Sciences, North China University of Science and Technology, Tangshan, China.
Bioinformatics. 2019 Aug 15;35(16):2796-2800. doi: 10.1093/bioinformatics/btz015.
DNA N6-methyladenine (6mA) is associated with a wide range of biological processes. Since the distribution of 6mA site in the genome is non-random, accurate identification of 6mA sites is crucial for understanding its biological functions. Although experimental methods have been proposed for this regard, they are still cost-ineffective for detecting 6mA site in genome-wide scope. Therefore, it is desirable to develop computational methods to facilitate the identification of 6mA site.
In this study, a computational method called i6mA-Pred was developed to identify 6mA sites in the rice genome, in which the optimal nucleotide chemical properties obtained by the using feature selection technique were used to encode the DNA sequences. It was observed that the i6mA-Pred yielded an accuracy of 83.13% in the jackknife test. Meanwhile, the performance of i6mA-Pred was also superior to other methods.
A user-friendly web-server, i6mA-Pred is freely accessible at http://lin-group.cn/server/i6mA-Pred.
DNA N6-甲基腺嘌呤（6mA）与广泛的生物学过程有关。由于基因组中 6mA 位点的分布是非随机的，因此准确识别 6mA 位点对于理解其生物学功能至关重要。尽管已经提出了用于这方面的实验方法，但它们在全基因组范围内检测 6mA 位点仍然成本效益不高。因此，开发计算方法来促进 6mA 位点的识别是可取的。
在这项研究中，开发了一种称为 i6mA-Pred 的计算方法来识别水稻基因组中的 6mA 位点，其中使用特征选择技术获得的最佳核苷酸化学性质用于编码 DNA 序列。观察到 i6mA-Pred 在 jackknife 测试中产生了 83.13%的准确率。同时，i6mA-Pred 的性能也优于其他方法。
一个用户友好的网络服务器，i6mA-Pred 可在 http://lin-group.cn/server/i6mA-Pred 上免费访问。
