Recognition of Protein-coding Genes Based on Z-curve Algorithms |
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| Authors: | Feng -Biao Guo Yan Lin Ling -Ling Chen |
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| Institution: | aCenter of Bioinformatics and Key Laboratory for NeuroInformation of the Ministry of Education, University of Elec-tronic Science and Technology of China, Chengdu, 610054, China;bDepartment of Physics, Tianjin University, Tianjin 300072, China;ccCollege of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China |
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| 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. |
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| Keywords: | Genome annotation Genome re-annotation Z-curve algorithm ZCURVE ZCURVE_V |
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