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Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

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).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...
Graphs of Equations in Two Variables01:30

Graphs of Equations in Two Variables

An equation with two variables, typically written in the form y = f(x) or Ax + By = C, describes a relationship between quantities represented by x and y. Each solution to such an equation is an ordered pair (x, y) that satisfies the equation when substituted. These pairs can be represented graphically to understand the variables' relationship visually.A common technique for constructing the graph of a two-variable equation is to create a value table. Begin by choosing several values for the...
Graphs of Functions01:30

Graphs of Functions

Graphs of functions provide a visual representation of how output values change in response to varying inputs. Each point on the graph corresponds to an ordered pair, where the x-coordinate (independent variable) determines the horizontal position and the y-coordinate (dependent variable) determines the vertical position. Linear functions like y = x give a straight line, indicating a constant rate of change.Nonlinear functions display more complex behaviors. Even power functions generate...
Graphs of Polar Equations01:17

Graphs of Polar Equations

The polar coordinate system represents points using a distance from a central point (the pole) and an angle from a reference direction (the polar axis). Unlike rectangular coordinates, polar coordinates are ideal for graphing curves with radial symmetry or periodic behavior.Some general forms of graphs in polar coordinates include the following:Equation of a Circle (Centered at the Pole):A graph where the radius remains constant for all angles traces a circle centered at the pole:Equation of a...
Graphs of Two-Variable Functions01:27

Graphs of Two-Variable Functions

A weather map provides a practical example of a function of two variables. Across a wide region such as the United States, temperatures vary from one location to another. Each location can be identified by two geographic coordinates: longitude and latitude. Since a single temperature value is assigned to each coordinate pair, the situation can be represented mathematically as a function with two inputs and one output.In mathematical notation, longitude and latitude can be labeled as x and y,...
Evolutionary Processes in Microbes01:26

Evolutionary Processes in Microbes

Microbial evolution occurs rapidly due to short generation times and a variety of genetic processes, including horizontal gene transfer, mutation, recombination, and genetic drift. These mechanisms collectively enable microbes to adapt swiftly to changing environments.Horizontal gene transfer (HGT) allows genes to move between different species and occurs through three main mechanisms: conjugation, transformation, and transduction. Conjugation involves direct cell-to-cell contact for DNA...

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関連する実験動画

Updated: Jun 20, 2026

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

Published on: December 7, 2021

グラフ上の進化の動態

Erez Lieberman1, Christoph Hauert, Martin A Nowak

  • 1Program for Evolutionary Dynamics, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA. erez@erez.com

Nature
|January 22, 2005
PubMed
まとめ
この要約は機械生成です。

進化グラフ理論は,ネットワーク上の集団をモデル化し,構造が選択にどのように影響するかを明らかにします. 特定のグラフ構造は選択を拡大または抑制し,進化的結果と固定確率に影響を与えます.

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

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Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli
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Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Published on: August 18, 2023

関連する実験動画

Last Updated: Jun 20, 2026

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

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli
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Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

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科学分野:

  • 進化生物学の進化生物学について
  • 数学生物学数学生物学について
  • ネットワーク科学 ネットワーク科学

背景:

  • 伝統的な進化動態学の研究では,均質または空間的に拡張された集団を想定しています.
  • 人口構造を一般化することは,多様な進化シナリオを理解するために極めて重要です.

研究 の 目的:

  • グラフで表現された一般化された人口構造の進化動態を調査する.
  • グラフのトポロジーとエッジ・ウェイトが固定確率と選択結果にどのように影響するか判断する.

主な方法:

  • 各種グラフタイプ (完全に接続された,空間的,ランダム,スケールフリー) で,個人を頂点として,生殖率を重み付きのエッジとしてモデル化します.
  • 異なる進化グラフ構造における突然変異体の固定確率を分析する.
  • 進化的ゲーム理論における周波数依存選択をグラフで調査する.

主要な成果:

  • 均質な集団を模倣するグラフ構造と,選択を抑制または増幅する構造を特定した.
  • 有利な変異体の固定を保証できるグラフを発見した.
  • グラフ構造が進化ゲームの結果を大きく変化させることを示した.

結論:

  • 進化グラフ理論は,進化のダイナミクスを一般化し分析するための強力な枠組みを提供します.
  • 人口構造は,進化の軌跡とゲーム結果の重要な決定因子です.
  • この発見は,生態学,多細胞組織,経済学に幅広い意味を持つ.