Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Population Growth00:57

Population Growth

29.2K
Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
29.2K
Genetic Drift03:33

Genetic Drift

44.6K
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.
44.6K
Modeling with Differential Equations01:25

Modeling with Differential Equations

133
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
133
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

77.0K
Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
77.0K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

65.1K
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).
65.1K
What is Population Genetics?01:25

What is Population Genetics?

65.2K
A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
65.2K

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Large language models instantiate evolutionarily robust strategies of cooperation.

PNAS nexus·2026
Same author

Topological Data Analysis in Materials Science: Principles, Machine Learning Integration, and Application Landscapes.

Chemical reviews·2026
Same author

Statistical learning of stochastic complex systems via the Yau-Yau nonlinear filter.

Innovation (Cambridge (Mass.))·2026
Same author

A deep-learning framework for brain tumor segmentation via three-dimensional mass-preserving geometric transformation.

Brain informatics·2026
Same author

Age distinguishes selection from causation in cancer genomes.

Nature genetics·2026
Same author

An end-to-end generalizable deep learning framework to comprehensively analyze transcriptional regulation.

Nature communications·2026
Same journal

Retraction Note: NSD2 targeting reverses plasticity and drug resistance in prostate cancer.

Nature·2026
Same journal

Enhanced B cell priming induces broadly neutralizing HIV-1 apex antibodies.

Nature·2026
Same journal

Vaccination elicits HIV broadly neutralizing antibodies in primates.

Nature·2026
Same journal

Child online safety needs more than social-media bans.

Nature·2026
Same journal

Ebola preparedness must start with ecosystems and before humans show symptoms.

Nature·2026
Same journal

AI tools can speed up thinking, but evidence still comes from the lab bench.

Nature·2026
関連記事をすべて見る

関連する実験動画

Updated: Mar 5, 2026

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

1.4K

人口構造の進化動態

Benjamin Allen1,2,3, Gabor Lippner3,4, Yu-Ting Chen2,3,5

  • 1Department of Mathematics, Emmanuel College, Boston, Massachusetts, USA.

Nature
|March 30, 2017
PubMed
まとめ
この要約は機械生成です。

構造化された集団における 進化のゲームダイナミクスは複雑です この研究は,強いペア接続を持つ集団で協力が繁栄し,弱い選択シナリオに新しい解決策を提供することを明らかにしています.

さらに関連する動画

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

9.2K
Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli
15:00

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

Published on: August 18, 2023

4.5K

関連する実験動画

Last Updated: Mar 5, 2026

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

1.4K
Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

9.2K
Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli
15:00

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

Published on: August 18, 2023

4.5K

科学分野:

  • 進化生物学
  • ゲーム理論
  • ネットワーク科学

背景:

  • 人口構造は進化の軌道を大きく左右する.
  • 一般的な構造化された集団における進化のゲームダイナミクスを理解することは,計算的に困難です.
  • 既存の数学的な解決策は 統一された接続性を持つ特定の集団構造に限定されています

研究 の 目的:

  • 弱い選択下で構造化された集団における進化的ゲームダイナミクスの一般的な解決策を開発する.
  • 人口の構造が協力の進化にどのように影響するかを調査する.
  • 任意のグラフやネットワーク構造に適用できる方法を提供する.

主な方法:

  • グラフ上のランダムな散歩の凝結時間を利用します.
  • 多様な人口構造を分析し 協力する傾向を評価する
  • 小規模な構造変化が進化の成果に及ぼす影響を研究するために,グラフ外科技術を使用します.

主要な成果:

  • 任意のグラフ上の進化ゲームにおける弱い選択のための新しい解決策が提示されています.
  • 協力は 強いカップル関係によって特徴づけられる集団で 最も繁栄していることが判明しました
  • この研究は,ネットワークトポロジが進化の安定性と協力レベルにどのように影響を与えるかを示しています.

結論:

  • 開発された方法は,複雑なネットワークにおける進化的ゲームダイナミクスを研究するための計算的に処理可能なアプローチを提供します.
  • 地域間の強い交流と 密集した地域社会は 協力の進化の重要な原動力です
  • 社会的行動を理解し 堅固な社会構造を設計する上で 重要な意味を持つことがわかりました