Recognition of Protein-coding Genes Based on Z-curve Algorithms
Feng-Biao Guo, Yan Lin and Ling-Ling Chen
Affiliation: College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.
Keywords: Genome annotation, Genome re-annotation, Z-curve algorithm, ZCURVE, ZCURVE_V.
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 Zcurve
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.
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