Prodigal: prokaryotic gene recognition and translation initiation site identification
Prodigal: prokaryotic gene recognition and translation initiation site identification
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DOI：
10.1186/1471-2105-11-119
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发表时间：
2010-03-08
影响因子：
3
通讯作者：
Hauser, Loren J.
中科院分区：
文献类型：
--
作者：
Hyatt, Doug;Chen, Gwo-Liang;Hauser, Loren J.
背景：在过去的十年中，微生物中的自动化基因预测的质量稳步提高，但仍有改进的空间。结果：根据我们多年为联合基因组研究所人工管理基因组的经验，我们开发了一种新的基因预测算法ProDigal(原核生物动态编程基因发现算法)。对于Prodigal，我们特别关注三个目标：改进的基因结构预测，改进的翻译起始位置识别，以及减少假阳性。结论：我们构建了一个快速、轻量级、开源的基因预测程序Prodigal http://compbio.ornl.gov/prodigal/.与现有的方法相比，Prodigal取得了很好的效果，我们相信它将是自动化微生物标注管道的宝贵资产。
Background: The quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals.Results: With our years of experience in manually curating genomes for the Joint Genome Institute, we developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm). With Prodigal, we focused specifically on the three goals of improved gene structure prediction, improved translation initiation site recognition, and reduced false positives. We compared the results of Prodigal to existing gene-finding methods to demonstrate that it met each of these objectives.Conclusion: We built a fast, lightweight, open source gene prediction program called Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines.