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Related Concept Videos

Phylogenetic Trees03:21

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.The length of the branches can depict time or the relative amount of change among organisms. For instance, the branch length might indicate the number of amino acid changes in the sequence that underlies the...
Phylogenetic Trees03:21

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.The length of the branches can depict time or the relative amount of change among organisms. For instance, the branch length might indicate the number of amino acid changes in the sequence that underlies the...
Phylogeny01:23

Phylogeny

Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Graphical Representation of Inequalities01:28

Graphical Representation of Inequalities

The graph of the equation where y equals x squared forms a curve known as a parabola. This curve acts as a boundary in the coordinate plane, dividing it into distinct regions based on the relative position of points.When the equality sign in the equation is replaced with an inequality—such as greater than, less than, greater than or equal to, or less than or equal to—the graphical representation changes from a single curve into a broader shaded area that signifies the set of all points...
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
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Related Experiment Video

Updated: Jun 12, 2026

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

Untangling tanglegrams: comparing trees by their drawings.

Balaji Venkatachalam1, Jim Apple, Katherine St John

  • 1Department of Computer Science, UC Davis, One Shields Avenue, Davis, CA 95616, USA. balaji@cs.ucdavis.edu

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|June 10, 2010
PubMed
Summary
This summary is machine-generated.

We present efficient algorithms for tanglegram drawing optimization. Our methods improve methods for minimizing crossings and introduce new criteria for analyzing biological evolutionary histories.

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Area of Science:

  • Computational biology
  • Graph theory
  • Algorithm design

Background:

  • Tanglegrams visualize relationships between two trees on the same set of leaves, crucial for comparing evolutionary histories in biology.
  • Applications include host-parasite coevolution and comparative genomics.

Purpose of the Study:

  • To develop efficient algorithms for tanglegram drawing optimization problems.
  • To address planarity testing, crossing minimization, and introduce new distance metrics.

Main Methods:

  • Reduction to planar graph drawing for planarity testing.
  • Graph crossing problem reductions for fixed-parameter tractable algorithms.
  • Development of O(n log n) and O(n²) algorithms for specific optimization tasks.
  • Integer programming formulations for practical drawing generation.

Main Results:

  • A linear time algorithm for tanglegram planarity testing.
  • A fixed-parameter tractable algorithm for minimizing crossings in d-ary trees.
  • An improved O(n log n) algorithm for minimizing crossings when one tree is fixed.
  • Introduction of Spearman's footrule distance for tanglegrams with an O(n²) algorithm.
  • Proof of lower bounds for a specific crossing minimization heuristic.

Conclusions:

  • The developed algorithms offer significant improvements in efficiency and scope for tanglegram analysis.
  • These methods provide powerful tools for comparative evolutionary studies and gene analysis.
  • The research advances the computational understanding of tanglegram representations and their applications.