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A benchmark of multiple sequence alignment programs upon structural RNAs

机译:基于结构RNA的多个序列比对程序的基准

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To date, few attempts have been made to benchmark the alignment algorithms upon nucleic acid sequences. Frequently, sophisticated PAM or BLOSUM like models are used to align proteins, yet equivalents are not considered for nucleic acids; instead, rather ad hoc models are generally favoured. Here, we systematically test the performance of existing alignment algorithms on structural RNAs. This work was aimed at achieving the following goals: (i) to determine conditions where it is appropriate to apply common sequence alignment methods to the structural RNA alignment problem. This indicates where and when researchers should consider augmenting the alignment process with auxiliary information, such as secondary structure and (ii) to determine which sequence alignment algorithms perform well under the broadest range of conditions. We find that sequence alignment alone, using the current algorithms, is generally inappropriate < 50-60% sequence identity. Second, we note that the probabilistic method ProAlign and the aging Clustal algorithms generally outperform other sequence-based algorithms, under the broadest range of applications.
机译:迄今为止,几乎没有尝试在核酸序列上对比对算法进行基准测试。通常,复杂的PAM或BLOSUM样模型用于比对蛋白质,但核酸不考虑等同物。相反,通常倾向于临时模型。在这里,我们系统地测试了结构RNA上现有比对算法的性能。这项工作旨在实现以下目标:(i)确定适合将常见序列比对方法应用于结构RNA比对问题的条件。这表明研究人员应在何时何地考虑使用辅助信息(例如二级结构)来增强比对过程,以及(ii)确定哪种序列比对算法在最宽泛的条件下表现良好。我们发现,仅使用当前算法进行序列比对通常不适合<50-60%的序列同一性。其次,我们注意到,在最广泛的应用范围内,概率方法ProAlign和老化的Clustal算法通常优于其他基于序列的算法。

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