Sivashankari Selvarajan, Shanmughavel Piramanayagam
Department of Bioinformatics, Kongunadu arts and science college, Coimbatore - 641029, India.
Bioinformation. 2006 Dec 29;1(8):335-8. doi: 10.6026/97320630001335.
The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress. The traditional biochemical/molecular experiments can assign accurate functions for genes in these genomes. However, the process is time-consuming and costly. Despite several efforts, only 50-60 % of genes have been annotated in most completely sequenced genomes. Automated genome sequence analysis and annotation may provide ways to understand genomes. Thus, determination of protein function is one of the challenging problems of the post-genome era. This demands bioinformatics to predict functions of un-annotated protein sequences by developing efficient tools. Here, we discuss some of the recent and popular approaches developed in Bioinformatics to predict functions for hypothetical proteins.
公共数据库中的完整人类基因组序列提供了理解生命蓝图的途径。截至2006年6月29日,已有27个古细菌、326个细菌和21个真核生物的完整基因组可供使用,另有316个细菌、24个古细菌、126个真核生物基因组的测序工作正在进行。传统的生化/分子实验能够为这些基因组中的基因确定准确的功能。然而,这个过程既耗时又昂贵。尽管已经做了很多努力,但在大多数已完全测序的基因组中,只有50%至60%的基因得到了注释。自动化的基因组序列分析和注释可能为理解基因组提供途径。因此,确定蛋白质功能是后基因组时代具有挑战性的问题之一。这就需要生物信息学通过开发高效工具来预测未注释蛋白质序列的功能。在这里,我们讨论一些生物信息学中最近开发的、流行的预测假设蛋白质功能的方法。