Building a small and informative phylogenetic supertree

IF 0.8 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS Information and Computation Pub Date : 2023-10-01 DOI:10.1016/j.ic.2023.105082
Jesper Jansson , Konstantinos Mampentzidis , Sandhya T.P.
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Abstract

We combine two fundamental optimization problems related to the construction of phylogenetic trees called maximum rooted triplets consistency and minimally resolved supertree into a new problem, which we call q-maximum rooted triplets consistency (q-MAXRTC). It takes as input a set R of rooted, binary phylogenetic trees with three leaves each and asks for a phylogenetic tree with exactly q internal nodes that contains the largest possible number of trees from R. We prove that q-MAXRTC is NP-hard to approximate within a constant, develop polynomial-time approximation algorithms for different values of q, and show experimentally that representing a phylogenetic tree by one having much fewer nodes typically does not destroy too much branching information. To demonstrate the algorithmic advantage of using trees with few internal nodes, we also propose a new algorithm for computing the rooted triplet distance that is faster than the existing algorithms when restricted to such trees.

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建立一个小而信息丰富的系统发育超树
我们将与构建系统发育树相关的两个基本优化问题(称为最大根三元组一致性和最小解超树)合并为一个新问题,称为q-最大根三联体一致性(q-MAXRTC)。它将一组R根二元系统发育树作为输入,每个树有三片叶子,并要求一个内部节点正好为q的系统发育树,该树包含R中尽可能多的树。我们证明了q-MAXRTC是NP难以在常数内近似的,针对不同的q值开发了多项式时间近似算法,并通过实验表明,用节点少得多的节点来表示系统发育树通常不会破坏太多的分支信息。为了证明使用内部节点较少的树的算法优势,我们还提出了一种计算有根三元组距离的新算法,该算法在局限于此类树时比现有算法更快。
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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
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