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

Median01:08

Median

30.1K
Besides mean, the median is a widely used measure of central tendency. Typically, median is defined as the central or middle value of a data set, measured by arranging the data elements in an increasing or decreasing order. Since this middle value is not affected by the precise numerical values of the outliers or fluctuations, it is insensitive to them. Hence, in cases where a data set may have outliers or the extreme values are not known, the median is a better measure of the central tendency...
30.1K
Sign Test for Median of Single Population01:20

Sign Test for Median of Single Population

379
In general, the sign test serves as a nonparametric method to test hypotheses about the median of a single population when the data does not follow a known distribution. This simplicity makes it particularly useful for small sample sizes or when the assumptions of parametric tests cannot be met. The process begins with identifying a null hypothesis, typically stating that the population median equals a specific value. The alternative hypothesis could be that the median is either not equal to,...
379
Survival Tree01:19

Survival Tree

443
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...
443
Distance Problem01:29

Distance Problem

93
When an object's velocity changes over time, the total distance traveled can be determined by summing small displacement intervals over short increments. This approach approximates the true distance through numerical summation and the use of integral calculus. An estimate of the total displacement can be obtained by measuring velocity at regular intervals and multiplying each value by the corresponding time step.If a runner accelerates over the first three seconds of a race, speed measurements...
93
Area Between Curves: Problem Solving01:27

Area Between Curves: Problem Solving

85
A region can be enclosed by three curves: a square root function, a reflected cube root function, and a linear function. The linear function intersects each of the other two curves, and these intersection points determine where the boundary of the enclosed region changes. Because different curves serve as the upper and lower boundaries in different parts of the graph, the area cannot be found using a single setup over the entire interval.To compute the area, the region is first divided into two...
85
Midpoint Rule01:20

Midpoint Rule

75
Approximating areas under curved boundaries is a common problem in applied mathematics, particularly when an exact calculation is difficult or impractical. One effective numerical method for this purpose is the Midpoint Rule, which provides an estimate of the area under a curve by using rectangular approximations over a specified interval.Description of the Midpoint RuleThe Midpoint Rule begins by dividing the given interval into a number of equal subintervals. For each subinterval, the...
75

You might also read

Related Articles

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

Sort by
Same author

A PLUM Job: Peptide modeLs for Understanding and engineering antiMicrobial therapeutics.

bioRxiv : the preprint server for biology·2026
Same author

Pathogenesis and Transmission of a Reassorted H1 Influenza A Virus Detected in North American Swine.

Influenza and other respiratory viruses·2026
Same author

Active surveillance for influenza A virus in swine reveals within-farm reassortment and cocirculation of distinct subtypes and genetic clades.

Veterinary microbiology·2025
Same author

Revealing Reassortment in Influenza A Viruses with TreeSort.

Molecular biology and evolution·2025
Same author

Phylo-rs: an extensible phylogenetic analysis library in rust.

BMC bioinformatics·2025
Same author

Transmission and Pathologic Findings of Divergent Human Seasonal H1N1pdm09 Influenza A Viruses Following Spillover Into Pigs in the United States.

Influenza and other respiratory viruses·2025
Same journal

circ2DGNN: circRNA-Disease Association Prediction via Transformer-Based Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Hierarchical Hypergraph Learning in Association- Weighted Heterogeneous Network for miRNA- Disease Association Identification.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Discriminative Domain Adaption Network for Simultaneously Removing Batch Effects and Annotating Cell Types in Single-Cell RNA-Seq.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

MLW-BFECF: A Multi-Weighted Dynamic Cascade Forest Based on Bilinear Feature Extraction for Predicting the Stage of Kidney Renal Clear Cell Carcinoma on Multi-Modal Gene Data.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Generative Biomedical Event Extraction With Constrained Decoding Strategy.

IEEE/ACM transactions on computational biology and bioinformatics·2024
See all related articles

Related Experiment Video

Updated: Feb 20, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

3.0K

Efficient Local Search for Euclidean Path-Difference Median Trees.

Alexey Markin, Oliver Eulenstein

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |October 17, 2017
    PubMed
    Summary
    This summary is machine-generated.

    Synthesizing large phylogenetic trees is crucial in evolutionary biology. This study introduces a faster algorithm and a hybrid heuristic for median tree problems, improving species tree reconstruction from empirical data.

    More Related Videos

    Foraging Path-length Protocol for Drosophila melanogaster Larvae
    07:26

    Foraging Path-length Protocol for Drosophila melanogaster Larvae

    Published on: April 23, 2016

    9.9K
    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

    695

    Related Experiment Videos

    Last Updated: Feb 20, 2026

    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
    08:12

    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

    Published on: March 1, 2022

    3.0K
    Foraging Path-length Protocol for Drosophila melanogaster Larvae
    07:26

    Foraging Path-length Protocol for Drosophila melanogaster Larvae

    Published on: April 23, 2016

    9.9K
    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

    695

    Area of Science:

    • Evolutionary Biology
    • Computational Biology
    • Phylogenetics

    Background:

    • Synthesizing large-scale phylogenetic trees is a fundamental challenge in evolutionary biology.
    • Median tree problems are powerful tools for reconstructing evolutionary histories from multiple input trees.
    • The path-difference distance is a commonly used metric for comparing phylogenetic trees.

    Purpose of the Study:

    • To develop a more efficient algorithm for the local search problem within median tree reconstruction.
    • To introduce a novel hybrid local search heuristic for improved phylogenetic tree synthesis.
    • To evaluate the performance of the new hybrid heuristic against existing methods using empirical data.

    Main Methods:

    • Devised a time-efficient algorithm for the local search problem in median tree reconstruction.
    • Improved upon the best-known solution for the local search problem by a factor of n.
    • Developed a novel hybrid local search heuristic incorporating the new algorithm.
    • Conducted a comparative study using published empirical datasets to assess heuristic performance.

    Main Results:

    • The new algorithm significantly improves the time efficiency of solving the local search problem.
    • The hybrid heuristic demonstrates enhanced performance in synthesizing species trees.
    • Comparative analysis shows the hybrid heuristic is competitive with or superior to commonly used methods.

    Conclusions:

    • The developed time-efficient algorithm and hybrid heuristic offer advancements in phylogenetic tree synthesis.
    • These methods provide more refined and effective tools for reconstructing evolutionary relationships.
    • The findings have practical implications for evolutionary biology research utilizing large-scale phylogenetic data.