Suppr超能文献

微生物中直系同源基因组的准确预测。

Accurate prediction of orthologous gene groups in microbes.

作者信息

Wu Hongwei, Mao Fenglou, Olman Victor, Xu Ying

机构信息

Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30622, USA.

出版信息

Proc IEEE Comput Syst Bioinform Conf. 2005:73-9. doi: 10.1109/csb.2005.10.

Abstract

We present a new computational method for the prediction of orthologous gene groups for microbial genomes based on the prediction of co-occurrences of homologous genes. The method is inspired by the observation that homologous genes are highly likely to be orthologous if their neighboring genes are also homologous. Based on co-occurrences of homologous genes, we have grouped the (predicted) operons of 77 selected sequenced microbial genomes so that operons of the same group are highly likely to be functionally similar or related. We then cluster the homologous genes in the same operon group so that genes of the same cluster are highly likely to be similar in terms of their sequences and functions, i.e., they are predicted to be orthologous genes. By comparing our predicted orthologous gene groups with the COG assignments and NCBI annotations, we conclude that our method is promising to provide more accurate and specific predictions than the existing methods.

摘要

我们提出了一种基于同源基因共现预测来预测微生物基因组直系同源基因组的新计算方法。该方法的灵感来源于这样的观察:如果同源基因的相邻基因也是同源的,那么这些同源基因极有可能是直系同源的。基于同源基因的共现情况,我们对77个选定的已测序微生物基因组的(预测)操纵子进行了分组,使得同一组的操纵子极有可能在功能上相似或相关。然后,我们将同一操纵子组中的同源基因进行聚类,使得同一簇中的基因在序列和功能方面极有可能相似,即它们被预测为直系同源基因。通过将我们预测的直系同源基因组与COG分类和NCBI注释进行比较,我们得出结论,与现有方法相比,我们的方法有望提供更准确、更具体的预测。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验