Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Survival Tree01:19

Survival Tree

499
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
499
Phylogenetic Trees03:21

Phylogenetic Trees

41.7K
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.
41.7K
Phylogenetic Trees03:21

Phylogenetic Trees

5.7K
5.7K
Theorems of Pappus and Guldinus: Problem Solving01:12

Theorems of Pappus and Guldinus: Problem Solving

1.2K
Pappus and Guldinus's theorems are powerful mathematical principles that are used for finding the surface area and volume of composite shapes. For example, consider a cylindrical storage tank with a conical top. Finding the surface area or volume can be challenging for such complex shapes. These theorems are particularly useful in calculating the volume and surface area of such systems. Here, the cylindrical storage tank with a conical top can be broken down into two simple shapes: a...
1.2K
Fundamental Theorem of Algebra01:30

Fundamental Theorem of Algebra

503
The Fundamental Theorem of Algebra is central to the study of polynomial equations, asserting that every non-constant polynomial with complex coefficients has at least one complex zero. This means that a polynomial of degree n ≥ 1, written as:  with an ≠ 0, has at least one solution in the complex number system. Since the set of real numbers is a subset of complex numbers, this theorem applies equally to polynomials with real coefficients.Building on this result, the...
503
Binomial Expansion Using Pascal's Triangle01:30

Binomial Expansion Using Pascal's Triangle

465
Expanding a binomial expression such as (a + b)n results in a predictable sequence of terms that can be systematically derived using Pascal’s Triangle. This triangular array of numbers plays a central role in understanding and computing the coefficients of binomial expansions.Pascal’s Triangle is constructed such that each row corresponds to the coefficients of a binomial raised to a power. The topmost row, known as the zeroth row, corresponds to (a + b)0, and each successive row...
465

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Two C++ libraries for counting trees on a phylogenetic terrace.

Bioinformatics (Oxford, England)·2018
Same author

Multi-rate Poisson tree processes for single-locus species delimitation under maximum likelihood and Markov chain Monte Carlo.

Bioinformatics (Oxford, England)·2017
Same author

Efficient Detection of Repeating Sites to Accelerate Phylogenetic Likelihood Calculations.

Systematic biology·2016
Same author

Effects of pre- and postnatal exposure to 1880-1900MHz DECT base radiation on development in the rat.

Reproductive toxicology (Elmsford, N.Y.)·2016
Same author

The levels of the GluN2A NMDA receptor subunit are modified in both the neonatal and adult rat brain by an early experience involving denial of maternal contact.

Neuroscience letters·2015
Same author

INSECT PHYLOGENOMICS. Response to Comment on "Phylogenomics resolves the timing and pattern of insect evolution".

Science (New York, N.Y.)·2015
Same journal

Inverse FIP effect plasma in the solar atmosphere: a synthesis of current understanding and new insights from AR 11967.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

Signs of sulfur fractionation under high magnetic field strength.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

First ionization potential fractionation of sulfur observed with spectral imaging of the coronal environment.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

Chromospheric dynamics and turbulence regulate the solar FIP effect.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

Exploring the link between wave activity in the photospheric velocity driver and the FIP bias in the solar corona.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same journal

Radiative hydrodynamic simulations of first ionization potential fractionation in solar flares.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
See all related articles

Related Experiment Video

Updated: May 1, 2026

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

1.9K

An optimal algorithm for computing all subtree repeats in trees.

T Flouri1, K Kobert, S P Pissis

  • 1Heidelberg Institute for Theoretical Studies, , 69118 Heidelberg, Germany.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|April 23, 2014
PubMed
Summary
This summary is machine-generated.

We developed a linear-time algorithm to group repeating subtrees in labelled trees. This method efficiently identifies equivalent subtrees based on topology and node labels for unrooted, unordered trees.

Keywords:
subtree repeatstree data structuresunrooted unordered labelled trees

More Related Videos

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

918
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.0K

Related Experiment Videos

Last Updated: May 1, 2026

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

1.9K
Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

918
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.0K

Area of Science:

  • Computer Science
  • Graph Theory
  • Algorithms

Background:

  • Identifying repeating substructures is crucial in analyzing complex data.
  • Tree structures are fundamental in various computational domains.
  • Efficient algorithms for subtree analysis are highly sought after.

Purpose of the Study:

  • To develop an efficient algorithm for grouping repeating subtrees in labelled trees.
  • To classify subtrees based on topology and node labels.
  • To achieve a time-optimal solution for this computational problem.

Main Methods:

  • An explicit, simple algorithm is presented for unrooted, unordered, labelled trees.
  • The algorithm's time complexity is analyzed.
  • The method's adaptability to rooted, ordered, or unlabelled trees is demonstrated.

Main Results:

  • A time-optimal algorithm with linear running time complexity (O(n)) relative to tree size is achieved.
  • The algorithm effectively groups repeating subtrees into equivalence classes.
  • The method is shown to be versatile and adaptable to various tree types.

Conclusions:

  • The presented algorithm provides an efficient and optimal solution for identifying and grouping repeating subtrees.
  • The algorithm's linear time complexity makes it suitable for large-scale tree analysis.
  • The adaptability of the algorithm broadens its applicability across different tree-related computational tasks.