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相关概念视频

Phylogenetic Trees03:21

Phylogenetic Trees

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Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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...
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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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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

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In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
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Phylogeny01:23

Phylogeny

43.5K
Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire kingdom.
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Updated: May 27, 2025

A Practical Guide to Phylogenetics for Nonexperts
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遗传学最小描述长度:基于算法复杂性的最佳性标准.

Ward C Wheeler1, Andres Varón1

  • 1Division of Invertebrate Zoology, American Museum of Natural History, 200 Central Park West, New York, NY, 10024, USA.

Cladistics : the international journal of the Willi Hennig Society
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PubMed
概括
此摘要是机器生成的。

遗传学最小描述长度 (PMDL) 提供了一种分析进化关系的新方法. 这种算法信息标准自然会权衡数据和模型类型,统一现有方法,并允许复杂的基因组图比较.

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科学领域:

  • 计算生物学 计算生物学
  • 进化生物学 进化生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 遗传学分析的目的是重建进化历史.
  • 现有的最佳性标准 (例如,节,概率) 在数据权重和模型选择方面存在局限性.
  • 需要一个统一的标准来解释家族遗传图的复杂性.

研究的目的:

  • 引入植物遗传学最小描述长度 (PMDL) 作为植物遗传学分析的新型最佳性标准.
  • 为了证明PMDL能够为各种类遗传数据和模型生成自然权重函数的能力.
  • 为了展示PMDL的能力,以结合家族遗传图的复杂性,以进行假设比较.

主要方法:

  • PMDL基于算法 (科尔摩戈罗夫) 信息理论和最小描述长度原则.
  • 开发了启发式方法来估计家族遗传学假设的不可计算的算法信息内容.
  • 在特定条件下,该标准被证明是普遍的,并与现有的推理方法趋同.

主要成果:

  • PMDL提供了一个统一的框架,自然地包含数据和模型权重.
  • 该标准允许比较涉及不同类型的遗传学图形 (树木,网络,森林) 的假设.
  • 通过PMDL,除了基因组图选择之外,还可以更轻松地选择分析模型,从而防止过度参数化.

结论:

  • PMDL代表了一种泛化和强大的最佳性标准,用于遗传学推断.
  • 它提供了一个以原则为基础的方法来选择模型和测试遗传学中的假设.
  • 启发式方法提供了应用PMDL的实际手段,尽管其理论上是不可计算的.