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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.

Author information

1
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.
2
Department of Physics, Tianjin University, Tianjin 300072, China.
3
cCollege of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.

Abstract

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.

KEYWORDS:

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

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