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Curr Genomics. 2014 Apr;15(2):95-103. doi: 10.2174/1389202915999140328162724.

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

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Center of Bioinformatics and Key Laboratory for NeuroInformation of the Ministry of Education, University of Elec-tronic Science and Technology of China, Chengdu, 610054, China.
Department of Physics, Tianjin University, Tianjin 300072, China.
cCollege of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.


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.


Genome annotation; Genome re-annotation; Z-curve algorithm; ZCURVE; ZCURVE_V.

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