A near-linear kernel for bounded-state parsimony distance

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE Journal of Computer and System Sciences Pub Date : 2023-09-26 DOI:10.1016/j.jcss.2023.103477
Elise Deen , Leo van Iersel , Remie Janssen , Mark Jones , Yukihiro Murakami , Norbert Zeh
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Abstract

The maximum parsimony distance dMP(T1,T2) and the bounded-state maximum parsimony distance dMPt(T1,T2) measure the difference between two phylogenetic trees T1,T2 in terms of the maximum difference between their parsimony scores for any character (with t a bound on the number of states in the character, in the case of dMPt(T1,T2)). While computing dMP(T1,T2) was previously shown to be fixed-parameter tractable with a linear kernel, no such result was known for dMPt(T1,T2). In this paper, we prove that computing dMPt(T1,T2) is fixed-parameter tractable for all t. Specifically, we prove that this problem has a kernel of size O(klgk), where k=dMPt(T1,T2). As the primary analysis tool, we introduce the concept of leg-disjoint incompatible quartets, which may be of independent interest.

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有界态简约距离的近线性核
最大简约距离dMP(T1,T2。虽然计算dMP(T1,T2)之前被证明是可以用线性核处理的固定参数,但对于dMP(T1,T2)没有这样的结果是已知的。在本文中,我们证明了计算dMPt(T1,T2)对于所有t都是可处理的固定参数。具体地,我们证明这个问题具有大小为O(klg⁡k) ,其中k=dMPt(T1,T2)。作为主要的分析工具,我们引入了腿不相交不相容四元组的概念,它可能具有独立的兴趣。
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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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