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Quasi-consensus-based comparison of profile hidden Markov models for protein sequences

机译:基于拟共识的蛋白质序列轮廓隐马尔可夫模型比较

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摘要

A simple approach for the sensitive detection of distant relationships among protein families and for sequence-structure alignment via comparison of hidden Markov models based on their quasi-consensus sequences is presented. Using a previously published benchmark dataset, the approach is demonstrated to give better homology detection and yield alignments with improved accuracy in comparison to an existing state-of-the-art dynamic programming profile-profile comparison method. This method also runs significantly faster and is therefore suitable for a server covering the rapidly increasing structure database. A server based on this method is available at http://liao.cis.udel.edu/website/servers/modmod.
机译:提出了一种简单的方法,可以通过比较基于隐性马尔可夫模型的准共识序列来敏感地检测蛋白质家族之间的远距离关系和进行序列结构比对。与现有的最新动态编程轮廓-轮廓比较方法相比,使用先前发布的基准数据集,该方法可提供更好的同源性检测和产量比对,并具有更高的准确性。此方法的运行速度也显着提高,因此适用于覆盖快速增长的结构数据库的服务器。基于此方法的服务器位于http://liao.cis.udel.edu/website/servers/modmod。

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