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

التفاصيل البيبلوغرافية
العنوان: Deep kernelization for the Tree Bisection and Reconnnect (TBR) distance in phylogenetics
المؤلفون: Kelk, Steven, Linz, Simone, Meuwese, Ruben
سنة النشر: 2022
المجموعة: Computer Science
Mathematics
Quantitative Biology
مصطلحات موضوعية: Computer Science - Data Structures and Algorithms, Mathematics - Combinatorics, Quantitative Biology - Populations and Evolution
الوصف: 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.
Comment: 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
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2206.04451
رقم الأكسشن: edsarx.2206.04451
قاعدة البيانات: arXiv