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Efficient Automatic Exact Motif Discovery Algorithms For Biological Sequences

机译:高效的生物序列自动精确基元发现算法

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Objective: This paper presents an algorithm for the solution of the motif discovery problem (MDP). Methods and materials: Motif discovery problem can be considered in two cases: motifs with insertions/ deletions, and motifs without insertions/deletions. The first group motifs can be found by stochastic and approximated methods. The second group can be found by using stochastic and approximated methods, but also deterministic method. We proved that the second group motifs can be found with a deterministic algorithm, and so, it can be said that the second motifs finding is a P-type problem as proved in this paper.rnResults and conclusions: An algorithm was proposed in this paper for motif discovery problem. The proposed algorithm finds all motifs which are occurred in the sequence at least two times, and it also finds motifs of various sizes. Due to this case, this algorithm is regarded as Automatic Exact Motif Discovery Algorithm. All motifs of different sizes can be found with this algorithm, and this case was proven in this paper. It shown that automatic exact motif discovery is a P-type problem in this paper. The application of the proposed algorithm has been shown that this algorithm is superior to MEME, MEME3, Motif Sampler, WEEDER, CONSENSUS, AlignACE.
机译:目的:本文提出了一种解决主题发现问题(MDP)的算法。方法和材料:可以在两种情况下考虑主题发现问题:带有插入/缺失的图案和没有插入/缺失的图案。第一组图案可以通过随机和近似方法找到。第二类可以使用随机和近似方法找到,也可以使用确定性方法找到。我们证明了可以使用确定性算法找到第二组图案,因此可以说,第二个图案的发现是本文证明的P型问题。rn结果与结论:本文提出了一种算法用于主题发现问题。所提出的算法找到了至少两次出现在序列中的所有图案,并且还找到了各种大小的图案。由于这种情况,该算法被视为自动精确基元发现算法。用这种算法可以找到所有大小不同的图案,这种情况在本文中得到了证明。研究表明,自动精确基序发现是一种P型问题。该算法的应用表明,该算法优于MEME,MEME3,Motif Sampler,WEEDER,CONSENSUS,AlignACE。

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