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Protein multiple sequence alignment benchmarking through secondary structure prediction

机译:通过二级结构预测进行蛋白质多序列比对基准测试

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摘要

MotivationMultiple sequence alignment (MSA) is commonly used to analyze sets of homologous protein or DNA sequences. This has lead to the development of many methods and packages for MSA over the past 30 years. Being able to compare different methods has been problematic and has relied on gold standard benchmark datasets of ‘true’ alignments or on MSA simulations. A number of protein benchmark datasets have been produced which rely on a combination of manual alignment and/or automated superposition of protein structures. These are either restricted to very small MSAs with few sequences or require manual alignment which can be subjective. In both cases, it remains very difficult to properly test MSAs of more than a few dozen sequences. PREFAB and HomFam both rely on using a small subset of sequences of known structure and do not fairly test the quality of a full MSA.
机译:动机多序列比对(MSA)通常用于分析同源蛋白质或DNA序列集。在过去的30年中,这导致了MSA的许多方法和软件包的开发。能够比较不同的方法一直存在问题,并依赖于“真实”比对的黄金标准基准数据集或MSA模拟。已经产生了许多蛋白质基准数据集,其依赖于蛋白质结构的手动比对和/或自动叠加的组合。这些要么限于序列很少的很小的MSA,要么需要手动比较,这可能是主观的。在这两种情况下,要正确测试多个序列的MSA仍然非常困难。 PREFAB和HomFam都依赖于使用已知结构序列的一小部分,并且不能公平地测试完整MSA的质量。

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