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arXiv 2508.03433cs.DS
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使用 de Bruijn 图进行字符串重构何时困难?

When is String Reconstruction using de Bruijn Graphs Hard?

Ben Bals, Sebastiaan van Krieken, Solon P. Pissis, Leen Stougie, Hilde Verbeek

AI总结:

本文研究从 de Bruijn 图重构字符串的难度,针对边区间约束的欧拉路径问题,提出参数化改进算法,证明当位置范围相对于 k 较小时问题可高效求解。

摘要:

将片段组装问题归约为(各种变体的)经典欧拉路径问题 [Pevzner 等人,PNAS 2001] 已导致基因组组装领域的显著进展。该归约使用了字母表 $\Sigma$ 上 $k$ 阶 de Bruijn 图 $G=(V,E)$ 的概念。$G$ 中的一条欧拉路径代表一个候选基因组重构。Bernardini 等人还在数据隐私领域引入了互补思想 [ALENEX 2020],该思想基于 $z$-匿名性。\n\n紧迫的问题是:给定一个模拟领域知识的函数,从 de Bruijn 图重构最佳字符串有多难?这样的函数将每个长度为 $k$ 的字符串映射到它在重构字符串中可能出现的区间。通过上述到 de Bruijn 图的归约,该函数转化为一个函数 $c$,它将每条边映射到它在欧拉路径中可能出现的区间。这引出了以下基本的图论问题:给定实例 $(G,c)$,我们能否高效地计算一条尊重 $c$ 的欧拉路径?Hannenhalli 等人 [CABIOS 1996] 形式化了该问题,并证明它是 NP-完全的。\n\n我们关注旨在通过复杂性捕获领域知识质量的参数化。Ben-Dor 等人开发了一种算法,在 $O(m \cdot w^{1.5} 4^{w})$ 时间内解决 de Bruijn 图上的该问题,其中 $m=|E|$,$w$ 是所有边上最大区间长度。Bumpus 和 Meeks [Algorithmica 2023] 在时间图上重新发现了相同的算法,突显了该问题在其他语境中的相关性。我们提供了组合学洞见,从而在指数时间上改进了现有技术。对于重要的 de Bruijn 图类,我们开发了一种以 $w (\log w+1) /(k-1)$ 为参数的算法。我们的改进算法表明,当位置范围相对于 $k$ 较小时,问题就足够简单。

英文摘要:

The reduction of the fragment assembly problem to (variations of) the classical Eulerian trail problem [Pevzner et al., PNAS 2001] has led to remarkable progress in genome assembly. This reduction employs the notion of de Bruijn graph $G=(V,E)$ of order $k$ over an alphabet $Σ$. A single Eulerian trail in $G$ represents a candidate genome reconstruction. Bernardini et al. have also introduced the complementary idea in data privacy [ALENEX 2020] based on $z$-anonymity. The pressing question is: How hard is it to reconstruct a best string from a de Bruijn graph given a function that models domain knowledge? Such a function maps every length-$k$ string to an interval of positions where it may occur in the reconstructed string. By the above reduction to de Bruijn graphs, the latter function translates into a function $c$ mapping every edge to an interval where it may occur in an Eulerian trail. This gives rise to the following basic problem on graphs: Given an instance $(G,c)$, can we efficiently compute an Eulerian trail respecting $c$? Hannenhalli et al.~[CABIOS 1996] formalized this problem and showed that it is NP-complete. We focus on parametrization aiming to capture the quality of our domain knowledge in the complexity. Ben-Dor et al. developed an algorithm to solve the problem on de Bruijn graphs in $O(m \cdot w^{1.5} 4^{w})$ time, where $m=|E|$ and $w$ is the maximum interval length over all edges. Bumpus and Meeks [Algorithmica 2023] rediscovered the same algorithm on temporal graphs, highlighting the relevance of this problem in other contexts. We give combinatorial insights that lead to exponential-time improvements over the state-of-the-art. For the important class of de Bruijn graphs, we develop an algorithm parametrized by $w (\log w+1) /(k-1)$. Our improved algorithm shows that it is enough when the range of positions is small relative to $k$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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