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

Migration00:53

Migration

7.9K
Migration is long-range, seasonal movement from one region or habitat to another. This common strategy, carried out by many different organisms around the world, is an adaptive response that typically corresponds to changes in an organism’s environment, like resource availability or climate. Migrations can involve huge groups of thousands of animals as well as single individuals traveling alone and can range from thousands of kilometers to just a few hundred meters.
7.9K
Improving Translational Accuracy02:07

Improving Translational Accuracy

10.2K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
10.2K
Constraints and Statical Determinacy01:26

Constraints and Statical Determinacy

603
In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
603
Gene Flow02:39

Gene Flow

35.1K
Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.
35.1K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

58.3K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
58.3K
Genetic Drift03:33

Genetic Drift

39.7K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
39.7K

You might also read

Related Articles

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

Sort by
Same author

Deconvolving Phylogenetic Distance Mixtures.

bioRxiv : the preprint server for biology·2026
Same author

Pharming: Joint Clonal Tree Reconstruction of Single-Nucleotide Variant and Copy Number Aberration Evolution from Single-Cell DNA Sequencing of Tumors.

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

A graph homomorphism approach for unraveling histories of metastatic cancers and viral outbreaks under evolutionary constraints.

Nature communications·2025
Same author

Fast tumor phylogeny regression via tree-structured dual dynamic programming.

Bioinformatics (Oxford, England)·2025
Same author

Evolution of gene order in prokaryotes is driven primarily by gene gain and loss.

bioRxiv : the preprint server for biology·2025
Same author

Evolution of gene order in prokaryotes is driven primarily by gene gain and loss.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same journal

GMSA: A Graph Matching and Point Cloud Registration-Based Method for Spatial Transcriptomics Data Alignment.

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

Investigations on Multiple Protein Scaffold Filling.

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

Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised Learning.

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

PPIGAN: Prediction of Protein-Protein Interactions Using Generative Adversarial Networks.

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

Deep Structure-Enhanced Cell Clustering Model for Single-Cell RNA Sequencing Data.

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

Asymmetric Drug-Drug Interaction Prediction Based on Generative Adversarial Networks and Knowledge Graph.

Journal of computational biology : a journal of computational molecular cell biology·2026
See all related articles

Related Experiment Video

Updated: Jun 26, 2025

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

5.9K

Enforcing Temporal Consistency in Migration History Inference.

Mrinmoy Saha Roddur1, Sagi Snir2, Mohammed El-Kebir1,3

  • 1Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, Illinois, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|May 16, 2024
PubMed
Summary
This summary is machine-generated.

This study addresses temporal inconsistencies in inferring biological migration histories, particularly for simultaneous comigrations. New methods ensure temporal consistency in phylogenetic trees, offering solutions for parsimonious consistent comigrations and migration history inference.

Keywords:
cancermetastasismigrationweak transmission bottleneck

More Related Videos

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.3K
Author Spotlight: Understanding Disease Mechanisms Through Real-Time Analysis of T-Cell Migration
06:42

Author Spotlight: Understanding Disease Mechanisms Through Real-Time Analysis of T-Cell Migration

Published on: May 24, 2024

1.4K

Related Experiment Videos

Last Updated: Jun 26, 2025

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

5.9K
Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.3K
Author Spotlight: Understanding Disease Mechanisms Through Real-Time Analysis of T-Cell Migration
06:42

Author Spotlight: Understanding Disease Mechanisms Through Real-Time Analysis of T-Cell Migration

Published on: May 24, 2024

1.4K

Area of Science:

  • Evolutionary Biology
  • Computational Biology
  • Phylogenetics

Background:

  • Biological populations migrate, influencing evolutionary trajectories.
  • Migration histories are often represented on phylogenetic trees.
  • Simultaneous comigration of multiple taxa presents unique challenges.

Purpose of the Study:

  • To identify and resolve temporal inconsistencies in inferring migration histories, especially those involving comigration.
  • To introduce precise definitions and algorithms for temporally consistent comigrations.
  • To develop methods for inferring parsimonious and temporally consistent migration histories.

Main Methods:

  • Formulation of the temporally consistent comigration problem with a linear time algorithm.
  • Definition and NP-hardness proof for the parsimonious consistent comigrations (PCC) problem.
  • Definition and NP-hardness proof for the parsimonious consistent comigration history (PCCH) problem.
  • Development of integer linear programming models for PCC and PCCH.

Main Results:

  • Demonstrated that previous parsimony-based methods can yield temporally inconsistent comigration solutions.
  • Provided a linear time algorithm for checking temporal consistency of comigrations.
  • Established the NP-hard nature of inferring parsimonious consistent comigrations and migration histories.
  • Successfully applied integer linear programming models to solve complex comigration problems.

Conclusions:

  • Ensuring temporal consistency is crucial for accurate phylogenetic migration inference.
  • The proposed methods and models offer robust solutions for analyzing comigration events.
  • The study advances the computational tools available for reconstructing complex evolutionary histories.