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Exact and approximation algorithms for the complementary maximal strip recovery problem

机译:互补最大带钢回收问题的精确算法和逼近算法

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摘要

Given two genomic maps G 1 and G 2 each represented as a sequence of n gene markers, the maximal strip recovery (MSR) problem is to retain the maximum number of markers in both G 1 and G 2 such that the resultant subsequences, denoted as G1*G_{1}^{*} and G2*G_{2}^{*}, can be partitioned into the same set of maximal substrings of length greater than or equal to two. Such substrings can occur in the reversal and negated form. The complementary maximal strip recovery (CMSR) problem is to delete the minimum number of markers from both G 1 and G 2 for the same purpose, with its optimization goal exactly complementary to maximizing the total number of gene markers retained in the final maximal substrings. Both MSR and CMSR have been shown NP-hard and APX-hard. A 4-approximation algorithm is known for the MSR problem, but no constant ratio approximation algorithm for CMSR. In this paper, we present an O(3 k n 2)-time fixed-parameter tractable (FPT) algorithm, where k is the size of the optimal solution, and a 3-approximation algorithm for the CMSR problem.
机译:给定两个基因组图G 1 和G 2 ,每个图由n个基因标记序列表示,最大条带回收率(MSR)问题是保留最大数目的标记。 G 1 和G 2 都这样,结果子序列表示为G 1 * G_ {1} ^ {*}和G 2 * G_ {2} ^ {*}可以划分为长度大于或等于2的同一组最大子串。这样的子串可以反转和否定的形式出现。互补最大条带回收(CMSR)问题是出于相同目的从G 1 和G 2 删除最小数量的标记,其优化目标与最大程度地保留最终最大子串中保留的基因标记总数。 MSR和CMSR均显示为NP-hard和APX-hard。对于MSR问题,已知一种4近似算法,但对于CMSR,没有恒定比率近似算法。在本文中,我们提出了O(3 k n 2 )次固定参数可处理时间(FPT)算法,其中k是最优解的大小,并且CMSR问题的3近似算法。

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