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相关概念视频

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.7K
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...
5.7K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
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Gene Flow02:39

Gene Flow

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Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.
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Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

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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.
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Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

58.0K
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).
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相关实验视频

Updated: Jun 4, 2025

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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MEGA12:分子进化遗传分析版本12适应性和绿色计算.

Sudhir Kumar1,2, Glen Stecher1, Michael Suleski1

  • 1Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA 19122, USA.

Molecular biology and evolution
|December 21, 2024
PubMed
概括
此摘要是机器生成的。

新的分子进化遗传学分析 (MEGA12) 软件通过优化模型选择和引导测试,显著加快了家族遗传学分析的速度. 这个版本增强了进化树推断,并使用稀疏学习识别了脆弱的分类,提高了计算效率而不牺牲准确性.

关键词:
启动链条 (bootstrap) 是一个启动链条.绿色计算是一种绿色计算.模型选择,模型选择.人类基因组学是什么?软件 软件 软件 软件 软件

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相关实验视频

Last Updated: Jun 4, 2025

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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科学领域:

  • 计算生物学 计算生物学
  • 进化遗传学 进化遗传学
  • 生物信息学是一种生物信息学.

背景情况:

  • 遗传学分析对于理解进化关系至关重要.
  • 对于大规模的基因组数据集,需要有效的计算方法.
  • 精确选择替代模型和强大的统计测试对于可靠的基因推理至关重要.

研究的目的:

  • 为了介绍分子进化遗传学分析 (MEGA12) 软件的第12个版本.
  • 在计算速度和分析能力方面显著改进.
  • 为了提高进化模式和脆弱类的识别在家族基因组分析.

主要方法:

  • 实施启发式学习来优化替代模型选择和最大概率 (ML) 族系的启动测试.
  • 整合一个进化的稀疏学习方法来识别脆弱的类.
  • 开发用于ML分析的细粒度并行化以及对Tree Explorer界面的增强.

主要成果:

  • 实质性减少了使用实现启发式启发式的基因分析的计算时间.
  • 结果的准确性证明与传统方法相比,尽管节省了时间.
  • 在族群基因组数据集中成功识别了脆弱的分类和相关序列.

结论:

  • MEGA12为分子进化和遗传学分析提供了一个计算效率高,准确的平台.
  • 新版本可以从大型数据集中更强大地推断进化关系.
  • MEGA12提供了先进的工具,用于探索进化模式,并识别潜在的不稳定的进化血统.