Hua Zhi-Gang, Lin Yan, Yuan Ya-Zhou, Yang De-Chang, Wei Wen, Guo Feng-Biao
Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China Health Big Data Science Research Center, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 610054, China Key Laboratory for NeuroInformation of the Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.
Department of Physics, Tianjin University, Tianjin 300072, China Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin 300072, China Collaborative Innovation Center of Chemical Science and Engineering, Tianjin 300072, China.
Nucleic Acids Res. 2015 Jul 1;43(W1):W85-90. doi: 10.1093/nar/gkv491. Epub 2015 May 14.
In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions.
2003年，我们开发了一个从头开始的程序ZCURVE 1.0，用于在细菌和古细菌基因组中寻找基因。在这项工作中，我们展示了更新版本（即ZCURVE 3.0）。使用422个原核生物基因组，更新版本的平均准确率为93.7%，而原始版本为88.7%。这些结果也表明ZCURVE 3.0与Glimmer 3.02相当，并且可以为其提供互补的预测。事实上，这两个程序的联合应用通过正确找到更多注释基因同时减少假阳性预测而产生了更好的结果。作为独特功能，ZCURVE 3.0包含一个后处理程序，该程序可以高精度（通常>90%）识别必需基因。我们希望ZCURVE 3.0将通过基于网络的运行模式得到广泛应用。更新后的ZCURVE可以从http://cefg.uestc.edu.cn/zcurve/ 或http://tubic.tju.edu.cn/zcurveb/免费无限制访问。
