ArticleBiology2013
Algorithms for computing the triplet and quartet distances for binary and general trees.
Article in Biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Computing generalized cophenetic distances under all Lp norms: A near-linear time algorithmic framework.PLoS computational biology · 2025Article
- DEPP: Deep Learning Enables Extending Species Trees using Single Genes.Systematic biology · 2023Article
- Log Transformation Improves Dating of Phylogenies.Molecular biology and evolution · 2021Article
- HIV-1 full-genome phylogenetics of generalized epidemics in sub-Saharan Africa: impact of missing nucleotide characters in next-generation sequences.AIDS research and human retroviruses · 2017Article
- Interspecific Plastome Recombination Reflects Ancient Reticulate Evolution in Picea (Pinaceae).Molecular biology and evolution · 2017Article
- Review Paper: The Shape of Phylogenetic Treespace.Systematic biology · 2017Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Distance measures between trees are useful for comparing trees in a systematic manner, and several different distance measures have been proposed. The triplet and quartet distances, for rooted and unrooted trees, respectively, are defined as the number of subsets of three or four leaves, respectively, where the topologies of the induced subtrees differ. These distances can trivially be computed by explicitly enumerating all sets of three or four leaves and testing if the topologies are different, but this leads to time complexities at least of the order n3 or n4 just for enumerating the sets. The different topologies can be counte dimplicitly, however, and in this paper, we review a series of algorithmic improvements that have been used during the last decade to develop more efficient algorithms by exploiting two different strategies for this; one based on dynamic programming and another based oncoloring leaves in one tree and updating a hierarchical decomposition of the other.
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Registered trials
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