4.3 Article

On cherry-picking and network containment

期刊

THEORETICAL COMPUTER SCIENCE
卷 856, 期 -, 页码 121-150

出版社

ELSEVIER
DOI: 10.1016/j.tcs.2020.12.031

关键词

Phylogenetic networks; Network containment; Cherry-picking sequences; Tree containment; Linear-time algorithms; Cherry-picking networks

资金

  1. Netherlands Organization for Scientific Research (NWO) [639.072.602]

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This paper introduces cherry-picking networks, a type of network that can be simplified by cherry-picking sequences. It demonstrates how to compare and distinguish these networks using their sequences. Additionally, it characterizes reconstructible cherry-picking networks and shows that the problem of checking network containment can be solved by computing cherry picking sequences in linear time.
Phylogenetic networks are used to represent evolutionary scenarios in biology and linguistics. To find the most probable scenario, it may be necessary to compare candidate networks. In particular, one needs to distinguish different networks and determine whether one network is contained in another. In this paper, we introduce cherry-picking networks, a class of networks that can be reduced by a so-called cherry-picking sequence. We then show how to compare such networks using their sequences. We characterize reconstructible cherry-picking networks, which are the networks that are uniquely determined by the sequences that reduce them, making them distinguishable. Furthermore, we show that a cherry-picking network is contained in another cherry picking network if a sequence for the latter network reduces the former network, provided both networks can be reconstructed from their sequences in a similar way (i.e., they are in the same reconstructible class). Lastly, we show that the converse of the above statement holds for tree-child networks, thereby showing that NETWORK CONTAINMENT, the problem of checking whether a network is contained in another, can be solved by computing cherry picking sequences in linear time for tree-child networks. (C) 2020 The Author(s). Published by Elsevier B.V.

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