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

Phylogenetic Trees03:21

Phylogenetic Trees

46.0K
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.
46.0K
Survival Tree01:19

Survival Tree

142
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...
142
Protein Networks02:26

Protein Networks

4.1K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.1K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.1K
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...
6.1K
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

83
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
83
Conservation of Small Populations02:04

Conservation of Small Populations

13.3K
Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
13.3K

You might also read

Related Articles

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

Sort by
Same author

Effects of transcranial direct current stimulation on cognition, depression, and brain activity in a breast-cancer survivor: a case report.

Journal of medical case reports·2026
Same author

Beyond Synteny: A Scalable Phylogenomics Method for Whole-Genome Duplication Detection.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same author

Quantifying Hierarchical Conflicts in Homology Statements.

Journal of molecular evolution·2025
Same author

A Probabilistic Algorithm for Gene-Species Reconciliation with Segmental Duplications.

Journal of computational biology : a journal of computational molecular cell biology·2025
Same author

Time to publish responsibly: DAFNEE, a database of academia-friendly journals in ecology and evolutionary biology.

Journal of evolutionary biology·2025
Same author

Lifestyle-Related Factors and Dietary Components that Affect the Risk of Prostate Cancer in a Brazilian Study Group.

Asian Pacific journal of cancer prevention : APJCP·2025
Same journal

A k-mer-based estimator of the substitution rate between repetitive sequences.

Algorithms for molecular biology : AMB·2026
Same journal

Haplotype-aware long-read error correction.

Algorithms for molecular biology : AMB·2026
Same journal

Extension of partial atom-to-atom maps: uniqueness and algorithms.

Algorithms for molecular biology : AMB·2026
Same journal

Lossless pangenome indexing using tag arrays.

Algorithms for molecular biology : AMB·2026
Same journal

Dolphyin: a combinatorial algorithm for identifying 1-Dollo phylogenies in cancer.

Algorithms for molecular biology : AMB·2026
Same journal

Probing transcription factor subsets in gene regulatory networks.

Algorithms for molecular biology : AMB·2026
See all related articles

Related Experiment Video

Updated: Aug 31, 2025

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.4K

Treewidth-based algorithms for the small parsimony problem on networks.

Celine Scornavacca1, Mathias Weller2

  • 1ISEM, Université de Montpellier, CNRS, IRD, EPHE, Montpellier, France.

Algorithms for Molecular Biology : AMB
|August 20, 2022
PubMed
Summary
This summary is machine-generated.

This study presents new algorithms for phylogenetic networks, efficiently calculating evolutionary character states. These methods improve upon existing approaches for parsimony scores on networks with low treewidth.

Keywords:
Dynamic programmingParameterized complexityParsimonyPhylogenetic networksPhylogeneticsTreewidth

More Related Videos

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
09:49

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

4.4K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.3K

Related Experiment Videos

Last Updated: Aug 31, 2025

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.4K
Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
09:49

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

4.4K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.3K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Phylogenetics

Background:

  • Phylogenetic reconstruction is a key challenge in bioinformatics.
  • The Small Parsimony problem is crucial for tree reconstruction but complex on networks with reticulate events.
  • Existing parsimony scores on networks are NP-hard, with algorithms parameterized by character states and reticulate events.

Purpose of the Study:

  • To develop efficient algorithms for the Small Parsimony problem on phylogenetic networks.
  • To address three proposed versions of parsimony scores on networks.
  • To leverage the treewidth parameter for algorithmic efficiency.

Main Methods:

  • Dynamic programming algorithms parameterized by treewidth.
  • Consideration of the treewidth of the underlying undirected graph of the network.
  • Formulation of treewidth-based dynamic programming for phylogenetic networks.

Main Results:

  • Algorithms for three versions of the parsimony problem on networks with running times dependent on treewidth.
  • Improved and subsumed previously known algorithms for these parsimony score variants.
  • A novel formulation of tree decompositions using "agreeing trees".

Conclusions:

  • Enables computation of popular parsimony scores on phylogenetic networks with low treewidth.
  • Enhances existing algorithms for parsimony score variants.
  • Aims to make treewidth-based algorithms more accessible to researchers in phylogenetic networks.