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Recognition of Protein-coding Genes Based on Z-curve Algorithms

机译:基于Z曲线算法的蛋白质编码基因识别

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摘要

Recognition of protein-coding genes, a classical bioinformatics issue, is an absolutely needed step for annotating newly sequenced genomes. The Z-curve algorithm, as one of the most effective methods on this issue, has been successfully applied in annotating or re-annotating many genomes, including those of bacteria, archaea and viruses. Two Z-curve based ab initio gene-finding programs have been developed: ZCURVE (for bacteria and archaea) and ZCURVE_V (for viruses and phages). ZCURVE_C (for 57 bacteria) and Zfisher (for any bacterium) are web servers for re-annotation of bacterial and archaeal genomes. The above four tools can be used for genome annotation or re-annotation, either independently or combined with the other gene-finding programs. In addition to recognizing protein-coding genes and exons, Z-curve algorithms are also effective in recognizing promoters and translation start sites. Here, we summarize the applications of Z-curve algorithms in gene finding and genome annotation.
机译:识别蛋白质编码基因是一个经典的生物信息学问题,是注释新测序基因组的绝对必要的步骤。 Z曲线算法是解决此问题的最有效方法之一,已成功用于注释或重新注释许多基因组,包括细菌,古细菌和病毒的基因组。已经开发了两个基于Z曲线的从头算基因的程序:ZCURVE(用于细菌和古细菌)和ZCURVE_V(用于病毒和噬菌体)。 ZCURVE_C(用于57个细菌)和Zfisher(用于任何细菌)是用于重新注释细菌和古细菌基因组的Web服务器。以上四个工具可以独立地或与其他基因发现程序结合用于基因组注释或重新注释。除了识别蛋白质编码基因和外显子外,Z曲线算法还可以有效识别启动子和翻译起始位点。在这里,我们总结了Z曲线算法在基因发现和基因组注释中的应用。

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