title: Recognition of Protein-coding Genes Based on Z-curve Algorithms.
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.
authors.affiliation: 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.
authors.forename: Feng
authors.initials: F
authors.lastname: -Biao Guo
authors.affiliation: Department of Physics, Tianjin University, Tianjin 300072, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Lin
authors.affiliation: cCollege of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.
authors.forename: Ling
authors.initials: L
authors.lastname: -Ling Chen
keywords: Genome annotation; Genome re-annotation; Z-curve algorithm; ZCURVE; ZCURVE_V.