Permutation-constrained Common String Partitions with Applications

IF 0.9 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Manuel Lafond, Binhai Zhu
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引用次数: 0

Abstract

We study a new combinatorial problem based on the famous Minimum Common String Partition problem, which we call Permutation-constrained Common String Partition (PCSP for short). In PCSP, we are given two sequences/genomes s and t with the same length and a permutation \(\pi \) on \([\ell ]\), the question is to decide whether it is possible to decompose s and t into \(\ell \) blocks that can be matched according to some specified requirements, and that conform with the permutation \(\pi \). Our main result is that PCSP is FPT in parameter \(\ell + d\), where d is the maximum number of occurrences that any symbol may have in s or t. We also study a variant where the input specifies whether each matched pair of block needs to be preserved as is, or reversed. With this result on PCSP, we show that a series of genome rearrangement problems are FPT \(k + d\), where k is the rearrangement distance between two genomes of interest.

Abstract Image

排列受限的普通字符串分区及其应用
我们在著名的最小公共字符串分割(Minimum Common String Partition)问题的基础上研究了一个新的组合问题,我们称之为 "排列约束公共字符串分割"(Permutation-constrained Common String Partition,简称 PCSP)。在 PCSP 中,我们给定了两个长度相同的序列/基因组 s 和 t,以及一个关于 \([\ell ]\) 的排列组合 \(\pi\),问题是要决定是否有可能把 s 和 t 分解成可以根据某些指定要求匹配的、符合排列组合 \(\pi\)的块(\(\ell \))。我们的主要结果是 PCSP 在参数 \(\ell + d\) 中是 FPT,其中 d 是任何符号在 s 或 t 中可能出现的最大次数。我们还研究了一种变体,即输入指定了每一对匹配的块是需要原样保留,还是需要反转。利用 PCSP 的这一结果,我们证明了一系列基因组重排问题都是 FPT \(k + d\) ,其中 k 是两个相关基因组之间的重排距离。
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来源期刊
Algorithmica
Algorithmica 工程技术-计算机:软件工程
CiteScore
2.80
自引率
9.10%
发文量
158
审稿时长
12 months
期刊介绍: Algorithmica is an international journal which publishes theoretical papers on algorithms that address problems arising in practical areas, and experimental papers of general appeal for practical importance or techniques. The development of algorithms is an integral part of computer science. The increasing complexity and scope of computer applications makes the design of efficient algorithms essential. Algorithmica covers algorithms in applied areas such as: VLSI, distributed computing, parallel processing, automated design, robotics, graphics, data base design, software tools, as well as algorithms in fundamental areas such as sorting, searching, data structures, computational geometry, and linear programming. In addition, the journal features two special sections: Application Experience, presenting findings obtained from applications of theoretical results to practical situations, and Problems, offering short papers presenting problems on selected topics of computer science.
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