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Segmented K-mer and its application on similarity analysis of mitochondrial genome sequences

机译:分段K聚体及其在线粒体基因组序列相似性分析中的应用

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K-mer-based approach has been widely used in similarity analyses so as to discover similarity/dissimilarity among different biological sequences. In this study, we have improved the traditional K-mer method, and introduce a segmented K-mer approach (s-K-mer). After each primary sequence is divided into several segments, we simultaneously transform all these segments into corresponding K-mer-based vectors. In this approach, it is vital how to determine the optimal combination of distance metric with the number of K and the number of segments, i.e., (K*s*and d*. Based on the cascaded feature vectors transformed from s* segmented sequences, we analyze 34 mammalian genome sequences using the proposed s-K-mer approach. Meanwhile, we compare the results of s-K-mer with those of traditional K-mer. The contrastive analysis results demonstrate that s-K-mer approach outperforms the traditionally K-mer method on similarity analysis among different species. ? 2012 Elsevier B.V.
机译:基于K-mer的方法已广泛用于相似性分析中,以发现不同生物学序列之间的相似性/不相似性。在这项研究中,我们改进了传统的K-mer方法,并引入了分段K-mer方法(s-K-mer)。在将每个主要序列划分为几个片段后,我们将所有这些片段同时转换为相应的基于K-mer的向量。在这种方法中,至关重要的是如何确定距离度量与K的数量和段的数量(即(K * s *和d *)的最佳组合。基于从s *分割序列转换而来的级联特征向量,我们使用建议的sK-mer方法分析了34个哺乳动物基因组序列,同时将sK-mer和传统K-mer的结果进行了比较,对比分析结果表明sK-mer方法优于传统的K-mer方法种之间相似性分析的方法。2012 Elsevier BV

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