Drawing (Complete) Binary Tanglegrams

Buchin, Kevin; Buchin, Maike; Byrka, Jarosław; Nöllenburg, Martin; Okamoto, Yoshio; Silveira, Rodrigo I.; Wolff, Alexander

doi:10.1007/978-3-642-00219-9_32

Cited by 16 publications

(8 citation statements)

References 22 publications

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“…The question is whether T 1 and T 2 admit a tanglegram drawing with at most k crossings among the tangles. In [4] it is shown that TTCM remains NP-complete even if the input trees are two complete binary trees of height h (hence, with 2 h leaves). We reduce this latter variant to RL.…”

Section: Minimizing the Number Of Crossingsmentioning

confidence: 99%

“…A phylogenetic tree is a full rooted binary tree (each node has zero or two children) representing the evolutionary relationships among related organisms. Biologists who study the co-evolution of species, such as hosts and parasites, start with a host phylogenetic tree H, a parasite tree P , and a mapping function ϕ (not necessarily injective nor surjective) from the leaves of P to the leaves of H. The triple H, P, ϕ , called co-phylogenetic tree, is traditionally represented with a tanglegram drawing, that consists of a pair of plane trees whose leaves are connected by straight-line edges [2,3,4,10,11,14,19]. However, a tanglegram only represents the input of a more complex process that aims at computing a mapping γ, called reconciliation, that extends ϕ and maps all the parasite nodes onto the host nodes.…”

Section: Introductionmentioning

confidence: 99%

“…A decade-old literature is devoted to tanglegram drawings (see e.g. [2,3,4,10,11,14,19]). Finding a tanglegram drawing that minimizes the number of crossings among the edges in E is known to be NPcomplete, even if the trees are binary trees or if the graph G is a matching [11].…”

Section: Introductionmentioning

confidence: 99%

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Visualizing co-phylogenetic reconciliations

Calamoneri

Donato

Mariottini

et al. 2020

Theoretical Computer Science

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We introduce a hybrid metaphor for the visualization of the reconciliations of co-phylogenetic trees, that are mappings among the nodes of two trees. The typical application is the visualization of the co-evolution of hosts and parasites in biology. Our strategy combines a space-filling and a node-link approach. Differently from traditional methods, it guarantees an unambiguous and 'downward' representation whenever the reconciliation is time-consistent (i.e., meaningful). We address the problem of the minimization of the number of crossings in the representation, by giving a characterization of planar instances and by establishing the complexity of the problem. Finally, we propose heuristics for computing representations with few crossings.

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Section: Minimizing the Number Of Crossingsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Visualizing co-phylogenetic reconciliations

Calamoneri

Donato

Mariottini

et al. 2020

Theoretical Computer Science

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“…However, when consulting the literature on tanglegrams, attention must be paid to the details. Some definitions require the trees to be binary, while others restrict the edge set to be a perfect matching, or both [7,11,27]. Since the focus of the paper is not on tanglegrams, we restrict ourselves to the general case.…”

Section: Introductionmentioning

confidence: 99%

Crossing Minimization in Storyline Visualization

Gronemann

Jünger

Liers

et al. 2016

Lecture Notes in Computer Science

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A storyline visualization is a layout that represents the temporal dynamics of social interactions along time by the convergence of chronological lines. Among the criteria oriented at improving aesthetics and legibility of a representation of this type, a small number of line crossings is the hardest to achieve. We model the crossing minimization in the storyline visualization problem as a multi-layer crossing minimization problem with tree constraints. Our algorithm can compute a layout with the minimum number of crossings of the chronological lines. Computational results demonstrate that it can solve instances with more than 100 interactions and with more than 100 chronological lines to optimality.

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“…Methods to compare different phylogenetic trees are based on dissimilarity or common information measurements. The dissimilarity methods include Robinson-Foulds (RF)[18], Tree-Bisection-Reconnect (TBR), Subtree-Prune-Regraft (SPR), Geodesic Tree Distance[19], Tanglegrams[20] and Rotation Distance [21]. The Common information model for tree comparison includes Maximum Common Refinement Subtree and Maximum agreement subtree[22].…”

Section: Introductionmentioning

confidence: 99%

Horizontal transfer in bacterial Methionyl tRNA synthetase is very common shown by Genus and phyla level phylogenetic analysis

Ghorpade

Pange²,

Sharma

2016

Preprint

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Methionyl tRNA synthetase is single copy informational gene in Salmonella typhimurium. Informational genes are more conserved than operational genes. In this study we had analyzed HGT events within MetG sequences of different bacterial genera. A species tree based on 16srRNA sequences of the same genus was drawn evaluated against the generally accepted species tree of the bacteria. MetG phylogenetic tree was evaluated against the 16srRNAS tree and HGT event identified. Similarly phyla trees were made and HGT event identified. 24 HGT events were identified between genus and 11 within phyla. MetG is a considered as conserved gene finding so many HGT event in this gene indicate that horizontal gene transfer is very common in this gene. Manual tree making for phyla could help to understand phylogenetic relationships between very large trees.Key Terms:-Methionyl tRNA synthetase, Topological difference, Robinson Fould Distance, MEGA.When the HGT was compared between phyla 11 HGT ( Fig.7) incidences were found, this suggest that HGT within phyla is less common than genus. It has been suggested that HGT is dependent on evolutionary distance [12,[41][42][43][44].Our results are in accordance with this fact. This is the first description of HGT within phyla and genus tree. Phyla level HGT by virtue of its relative simplistic network in comparison to genus network may help to understand jumbled network created by intensive gene transfer events which some author predict could replace classical rRNA based phylogeny [10, 11, 45, 46]. Materials and Methods:- Retrieval of MetG Sequences:-Salmonella enterica subsp. Entericaserovar Typhimurium genome sequence and other 57 amino acid sequences in fasta file format were retrieved from NCBI.The 16SrRNA for creating species phylogeny for corresponding genus mentioned in metG sequences were downloaded from Ribosomal Database-Silva from www.arb-silva.de [28]. Alignment of MetG and 16SrRNA sequences:-The alignments of sequences were performed in MEGA [29] using Muscle. Unaligned region of alignment were removed. The Evolutionary analysisEvolutionary analysis was done in MEGA [30][31][32] and the methods used were Maximum Likelihood tree, Neighbour Joning tree, Minimum Evolution tree, Maximum Parsimony tree and UPGMA.Test of reliability was Bootstrap method[33]with 500 replications. In order to keep things simple we have kept captions givenin MEGA with minor changes for each figures to get information regarding methodology of tree analysis.

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Drawing (Complete) Binary Tanglegrams

Cited by 16 publications

References 22 publications

Visualizing co-phylogenetic reconciliations

Visualizing co-phylogenetic reconciliations

Crossing Minimization in Storyline Visualization

Horizontal transfer in bacterial Methionyl tRNA synthetase is very common shown by Genus and phyla level phylogenetic analysis

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