An Improved Heuristic Algorithm for Finding Motif Signals in DNA Sequences

Huang Chao-Wen; Lee Wun-Shiun; Hsieh Sun-Yuan

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An Improved Heuristic Algorithm for Finding Motif Signals in DNA Sequences

机译：在DNA序列中寻找基序信号的改进启发式算法

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摘要

The planted (l,d)-motif search problem is a mathematical abstraction of the DNA functional site discovery task. In this paper, we propose a heuristic algorithm that can find planted (l,d)-signals in a given set of DNA sequences. Evaluations on simulated data sets demonstrate that the proposed algorithm outperforms current widely used motif finding algorithms. We also report the results of experiments on real biological data sets.

机译：植入的（l，d）-基序搜索问题是DNA功能位点发现任务的数学抽象。在本文中，我们提出了一种启发式算法，该算法可以在给定的DNA序列集中找到种植的（l，d）信号。对模拟数据集的评估表明，该算法优于目前广泛使用的主题查找算法。我们还报告了真实生物学数据集的实验结果。

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《Computational Biology and Bioinformatics, IEEE/ACM Transactions on》 |2011年第4期|p.959-975|共17页
作者
Huang Chao-Wen; Lee Wun-Shiun; Hsieh Sun-Yuan;
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National Cheng Kung University, Tainan;

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正文语种 eng
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关键词
(l; Planted motif search problem; d)-signals.; heuristic algorithms;

机译：（l;计划的主题搜索问题;d）-信号;启发式算法;

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专利

1. A multi-objective imperialist competitive algorithm (MOICA) for finding motifs in DNA sequences [J] . Gohardani Saeed Alirezanejad, Bagherian Mehri, Vaziri Hamidreza Annals of the American Thoracic Society . 2019,第3期

机译：一种多目标帝国主义竞争算法（MOICA）用于在DNA序列中寻找基序
2. Motif Discovery in DNA Sequences Using an Improved Gibbs (i Gibbs) Sampling Algorithm [J] . Makolo AU, Lamidi UA Journal of Computer Science & Systems Biology . 2018,第5期

机译：使用改进的Gibbs（i Gibbs）采样算法发现DNA序列中的基序
3. Memetic algorithms for de novo motif-finding in biomedical sequences [J] . Chengpeng Bi Artificial intelligence in medicine . 2012,第1期

机译：用于从头开始寻找生物医学序列的模因算法
4. Improved Pattern-Driven Algorithms for Motif Finding in DNA Sequences [C] . Sing-Hoi Sze, Xiaoyan Zhao Joint Annual RECOMB Satellite Workshop on Systems Biology and Regulatory Genomics . 2007

机译：改进的模式驱动算法用于DNA序列中的基序
5. A particle swarm optimization algorithm for finding DNA sequence motifs [D] . Lei, Chengwei 2008

机译：寻找DNA序列基序的粒子群优化算法
6. A niched Pareto genetic algorithm for finding variable length regulatory motifs in DNA sequences [O] . Shripal Vijayvargiya, Pratyoosh Shukla 2012

机译：一种在DNA序列中发现可变长度调控基序的小生境Pareto遗传算法
7. Figure 4: (A) One conserved sequence, which occurs 79 times in 46,264 binding site peaks from the ChIP-seq data-set. The mutation profile of this conserved sequence is illustrated, where ’_ ’ indicates this base is unchanged; DEL indicates this base is lost; INS X indicates a new base X is inserted in front of this base. (B) Several repeated elements patterns are listed. (C) In the first column, the top five DNA motifs, mined by meme-chip tools (Machanick Bailey, 2011) are illustrated. The resemblant conserved sequences, found by the CFSP algorithm are listed in the second column. In the third column, the position-specific scoring matrices, which are transformed from mutational information are listed. The similarity between meme motif and resemblant conserved sequence with PSSM format was calculated via a stamp motif comparison tool (Mahony Benos, 2007). The E-values for the similarity of those pairs is displayed in the fourth column. (D) One motif is selected in each group clustered by gkmsvm descriptors, and the corresponding motif found by the CFSP algorithm is listed below. (E) There are additional datasets (File No: ENCFF100GRL, ENCFF616IRT, ENCFF870CER, Target: SREBF1) collected from https://www.encodeproject.org. The top two motifs are selected in each file using meme tools, and the corresponding motifs found by our algorithm are listed below. [O] . -1

机译：图4：（a）一种保守序列，其发生在芯片-SEQ数据集中的46,264个结合位点峰值中的79倍。说明了这种保守序列的突变分布，其中'_'表示该碱度不变; del表示此基础丢失; INS X表示新的基础X插入此基础前面。（b）列出了几种重复的元素模式。（c）在第一栏中，示出了由MEME芯片工具（Machanick＆Bailey，2011）开采的前五个DNA主题。由CFSP算法发现的相应保守序列列于第二列中。在第三列中，列出了从突变信息转换的特定位置的评分矩阵。 MEME主题与PSSM格式的相似性与PSSM格式之间的相似性通过邮票图章比较工具（Mahony＆Benos，2007）计算。这些对相似性的电子值显示在第四列中。（d）在由GKMSVM描述符聚集的每个组中选择了一个图案，下面列出了CFSP算法的相应主题。（e）从https://www.encodeproject.org收集的，有附加数据集（文件no：cernff100grl，cenf616irl，conf8.20cer，target：srebf1）。使用MEME工具在每个文件中选择前两个图案，并且我们的算法发现的相应主题如下所示。
8. CWINNOWER Algorithm for Finding Fuzzy DNA Motifs [R] . Liang, S. 2003

机译：用于求模糊DNa图案的CWINNOWER算法

An Improved Heuristic Algorithm for Finding Motif Signals in DNA Sequences

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