一种改进的变长DNA基序发现算法

S. Islam, Md Rashed Asger, Md. Abid Hasan, M. Mottalib
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引用次数: 4

摘要

基序是在进化过程中自我保存的有意义的短序列,基序的发现是将DNA序列划分到相应类别的依据。不同的进化方法被用于基序发现,如遗传算法、粒子群算法等。在本文中,我们已经纳入了线性pso的概念,从DNA序列中寻找基序。然而,线性粒子群算法是一种较慢的方法,它涉及到对基序发现的线性搜索。因此,我们引入了索引表的功能,使motif的发现速度更快。在将目标基序(在每个循环中由Linear-PSO选择的粒子)与其他DNA序列进行线性比较之前,我们首先创建了一个索引表,其中包含每个目标基序的第一碱基索引信息。借助索引表进行识别,减少了motif发现所需的时间。实验结果表明,该方法具有较高的有效性和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modified algorithm for variable length DNA motif discovery
Motifs are meaningful short sequences which conserve itself during the evolution and discovery of motifs are used to put DNA sequences into their corresponding categories. Different evolutionary methods have been used for motif discovery i.e. genetic algorithm, PSO etc. In this paper we have incorporated the concept of Linear-PSO to find motifs from DNA sequences. However, Linear-PSO is a slower method which involves linear search for motif discovery. So we have introduced the function of index table to make the motif discovery faster. Before comparing the target motif (a particle selected by Linear-PSO in each cycle) linearly with other DNA sequences, we have first created an index table that contains the information about the index of first base of each of the target motifs. Identifying with the help of index table has lessened the time required for motif discovery. Experimental results show that the proposed method can discover motifs with higher validity and better efficiency.
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