Approximation algorithm for rearrangement distances considering repeated genes and intergenic regions.

IF 1.5 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Gabriel Siqueira, Alexsandro Oliveira Alexandrino, Andre Rodrigues Oliveira, Zanoni Dias
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引用次数: 2

Abstract

The rearrangement distance is a method to compare genomes of different species. Such distance is the number of rearrangement events necessary to transform one genome into another. Two commonly studied events are the transposition, which exchanges two consecutive blocks of the genome, and the reversal, which reverts a block of the genome. When dealing with such problems, seminal works represented genomes as sequences of genes without repetition. More realistic models started to consider gene repetition or the presence of intergenic regions, sequences of nucleotides between genes and in the extremities of the genome. This work explores the transposition and reversal events applied in a genome representation considering both gene repetition and intergenic regions. We define two problems called Minimum Common Intergenic String Partition and Reverse Minimum Common Intergenic String Partition. Using a relation with these two problems, we show a [Formula: see text]-approximation for the Intergenic Transposition Distance, the Intergenic Reversal Distance, and the Intergenic Reversal and Transposition Distance problems, where k is the maximum number of copies of a gene in the genomes. Our practical experiments on simulated genomes show that the use of partitions improves the estimates for the distances.

Abstract Image

Abstract Image

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考虑重复基因和基因间区域的重排距离逼近算法。
重排距离是比较不同物种基因组的一种方法。这个距离是将一个基因组转化为另一个基因组所必需的重排事件的数量。两种常见的研究事件是转位,即交换两个连续的基因组块,以及反转,即恢复基因组块。在处理这些问题时,开创性的工作将基因组表示为没有重复的基因序列。更现实的模型开始考虑基因重复或基因间区域的存在,基因之间和基因组末端的核苷酸序列。这项工作探讨了在考虑基因重复和基因间区域的基因组表示中应用的转位和反转事件。我们定义了最小公共基因间字符串划分和反向最小公共基因间字符串划分两个问题。利用这两个问题的关系,我们展示了一个[公式:见文本]-基因间转位距离,基因间反转距离,以及基因间反转和转位距离问题的近似值,其中k是基因组中基因的最大拷贝数。我们在模拟基因组上的实际实验表明,使用分区可以提高对距离的估计。
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来源期刊
Algorithms for Molecular Biology
Algorithms for Molecular Biology 生物-生化研究方法
CiteScore
2.40
自引率
10.00%
发文量
16
审稿时长
>12 weeks
期刊介绍: Algorithms for Molecular Biology publishes articles on novel algorithms for biological sequence and structure analysis, phylogeny reconstruction, and combinatorial algorithms and machine learning. Areas of interest include but are not limited to: algorithms for RNA and protein structure analysis, gene prediction and genome analysis, comparative sequence analysis and alignment, phylogeny, gene expression, machine learning, and combinatorial algorithms. Where appropriate, manuscripts should describe applications to real-world data. However, pure algorithm papers are also welcome if future applications to biological data are to be expected, or if they address complexity or approximation issues of novel computational problems in molecular biology. Articles about novel software tools will be considered for publication if they contain some algorithmically interesting aspects.
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