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PairMotif+: A fast and effective algorithm for de novo motif discovery in DNA sequences

机译:PairMotif +:快速有效的从头序列发现DNA序列的算法

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摘要

The planted (l, d) motif search is one of the most widely studied problems in bioinformatics, which plays an important role in the identification of transcription factor binding sites in DNA sequences. However, it is still a challenging task to identify highly degenerate motifs, since current algorithms either output the exact results with a high computational cost or accomplish the computation in a short time but very often fall into a local optimum. In order to make a better trade-off between accuracy and efficiency, we propose a new pattern-driven algorithm, named PairMotif+. At first, some pairs of l-mers are extracted from input sequences according to probabilistic analysis and statistical method so that one or more pairs of motif instances are included in them. Then an approximate strategy for refining pairs of l-mers with high accuracy is adopted in order to avoid the verification of most candidate motifs. Experimental results on the simulated data show that PairMotif+ can solve various (l, d) problems within an hour on a PC with 2.67 GHz processor, and has a better identification accuracy than the compared algorithms MEME, AlignACE and VINE. Also, the validity of the proposed algorithm is tested on multiple real data sets.
机译:植入的(l,d)基序搜索是生物信息学中研究最广泛的问题之一,它在DNA序列中转录因子结合位点的鉴定中起着重要作用。但是,识别高度退化的图案仍然是一项艰巨的任务,因为当前的算法要么以较高的计算成本输出精确的结果,要么在短时间内完成计算,但通常会陷入局部最优。为了在准确性和效率之间取得更好的平衡,我们提出了一种新的模式驱动算法,称为PairMotif +。首先,根据概率分析和统计方法从输入序列中提取几对l-mer,从而将一对或多对基序实例包括在其中。然后采用一种近似策略,以高精度精制一对l-mer,以避免验证大多数候选基序。在模拟数据上的实验结果表明,PairMotif +可以在具有2.67 GHz处理器的PC上在一小时内解决各种(l,d)问题,并且比比较算法MEME,AlignACE和VINE具有更好的识别精度。同样,在多个真实数据集上测试了所提出算法的有效性。

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