非编码RNA基因发现的联合协方差模型

Wenbo Jiang, K. Wiese
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引用次数: 5

摘要

利用协方差模型在基因组序列数据库中寻找非编码RNA基因成员已在许多研究中被证明是非常有效的。然而,它有一个明显的缺点,那就是非常大的计算负担。为了降低一个基因组序列中多个ncRNA基因家族的搜索复杂度,提出了一种组合协方差模型。使用分层聚类算法选择组合的协方差模型。本研究表明,当将少量原始协方差模型组合在一起时,组合的协方差模型可以找到所有原始ncRNA家族的成员,从而成功地减少了搜索时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combined covariance model for non-coding RNA gene finding
The use of covariance models in finding non-coding RNA gene members in genome sequence databases has been shown quite effective in many studies. However, it has a significant drawback, which is the very large computational burden. A combined covariance model is proposed to reduce the search complexity when a genome sequence is searched for more than one ncRNA gene family. The covariance models that are combined are selected using a hierarchical clustering algorithm. This study shows that when a small number of original covariance models are combined, the combined covariance model can find members from all original ncRNA families thus successfully reducing the search time.
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