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Chromatographic Resolution

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Updated: Jun 13, 2025

Concentric Gel System to Study the Biophysical Role of Matrix Microenvironment on 3D Cell Migration

Concentric Gel System to Study the Biophysical Role of Matrix Microenvironment on 3D Cell Migration

Published on: April 3, 2015

Fine-Resolution Asymmetric Migration Estimation.

Hao Shen¹, John Novembre^1,2

¹Department of Human Genetics, University of Chicago.

Biorxiv : the Preprint Server for Biology

|June 12, 2025

Summary

This summary is machine-generated.

A new method, FRAME, efficiently estimates asymmetric gene flow between populations. This allows for more detailed analysis of genetic structure, even with many subpopulations.

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Last Updated: Jun 13, 2025

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Analysis of Shear Flow-induced Migration of Murine Marginal Zone B Cells In Vitro

Analysis of Shear Flow-induced Migration of Murine Marginal Zone B Cells In Vitro

Published on: November 26, 2018

Area of Science:

Population genetics
Computational biology
Evolutionary biology

Background:

Gene flow asymmetries shape population genetic structure.
Existing methods like EEMS/FEEMS assume symmetric migration, limiting analysis of asymmetric gene flow.
Computationally intensive methods restrict asymmetric gene flow inference to small population sets.

Purpose of the Study:

Introduce FRAME (Fine-Resolution Asymmetric Migration Estimation), a computationally efficient method for inferring asymmetric gene flow.
Enable fine-scale population structure analyses with a large number of demes.
Provide a richer representation of genetic structure by detecting and summarizing gene flow asymmetries.

Main Methods:

Developed FRAME, a novel method reducing computational burden for asymmetric gene flow estimation.
Applied FRAME to simulated gene flow histories.
Validated FRAME using empirical datasets from gray wolves, poplar trees, white-crowned mannakin, and human archaeogenetics.

Main Results:

FRAME significantly reduces computational cost, enabling large-scale asymmetric gene flow analyses.
The method accurately infers asymmetric migration patterns under equilibrium and non-equilibrium conditions.
FRAME's estimates can be interpreted as backward migration rates under equilibrium.

Conclusions:

FRAME offers a scalable and flexible approach to detect complex asymmetric migration signals.
The method enhances the understanding of population genetic structure shaped by asymmetric gene flow.
FRAME's efficiency opens new avenues for fine-scale population genetic research.