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Journal of Computer and System Sciences
Article . 2024 . Peer-reviewed
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Article . 2022
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Deep kernelization for the Tree Bisection and Reconnection (TBR) distance in phylogenetics

Deep kernelization for the tree bisection and reconnection (TBR) distance in phylogenetics
Authors: Steven Kelk; Simone Linz; Ruben Meuwese;

Deep kernelization for the Tree Bisection and Reconnection (TBR) distance in phylogenetics

Abstract

We describe a kernel of size 9k-8 for the NP-hard problem of computing the Tree Bisection and Reconnect (TBR) distance k between two unrooted binary phylogenetic trees. We achieve this by extending the existing portfolio of reduction rules with three novel new reduction rules. Two of the rules are based on the idea of topologically transforming the trees in a distance-preserving way in order to guarantee execution of earlier reduction rules. The third rule extends the local neighbourhood approach introduced in (Kelk and Linz, Annals of Combinatorics 24(3), 2020) to more global structures, allowing new situations to be identified when deletion of a leaf definitely reduces the TBR distance by one. The bound on the kernel size is tight up to an additive term. Our results also apply to the equivalent problem of computing a Maximum Agreement Forest (MAF) between two unrooted binary phylogenetic trees. We anticipate that our results will be more widely applicable for computing agreement-forest based dissimilarity measures.

38 pages. In this version a figure has been added, some references have been added, some small typo's have been fixed and the introduction and conclusion have been slightly extended. Submitted for journal review

Country
Netherlands
Keywords

FOS: Computer and information sciences, TBR distance, agreement forest, Populations and Evolution (q-bio.PE), Computer science, Phylogenetics, phylogenetics, fixed parameter tractability, FOS: Biological sciences, kernelization, Computer Science - Data Structures and Algorithms, Fixed parameter tractability, FOS: Mathematics, Mathematics - Combinatorics, Kernelization, Data Structures and Algorithms (cs.DS), Combinatorics (math.CO), Quantitative Biology - Populations and Evolution, Agreement forest

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Top 10%
Green
hybrid