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相关概念视频

Phylogenetic Trees03:21

Phylogenetic Trees

50.5K
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.
50.5K
Phylogeny01:23

Phylogeny

63.8K
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.
63.8K
Parallel Processing01:20

Parallel Processing

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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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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...
7.1K
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 Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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相关实验视频

Updated: Mar 4, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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张量核解锁了在家族遗传树上的高效和低能量的大规模并行化.

Karthik Gangavarapu1, Xiang Ji2, Yucai Shao3

  • 1Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, California, USA.

Systematic biology
|March 3, 2026
PubMed
概括

植物遗传学的新算法将图形处理器 (GPU) 上的进化分析加速2-3倍. 这些方法还减少了能源消耗,使进化计算更具可持续性.

关键词:
贝叶斯的家族遗传学我们的GPU是GPU的GPU平行计算是平行计算.张量核的核心是张量核.

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科学领域:

  • 进化生物学是进化的生物学.
  • 计算生物学是一种计算生物学.
  • 生物信息学是一种生物信息学.

背景情况:

  • 图形处理单元 (GPU) 通过加速复杂的计算,彻底改变了统计学遗传学.
  • GPU 硬件的进步需要新的算法来最大限度地提高进化分析中的性能.

研究的目的:

  • 引入新的算法,利用NVIDIA GPU上的张量核心来实现更快的基因推理.
  • 改进进化模型中概率及其梯度的计算.

主要方法:

  • 开发了使用GPU张量核加速矩阵乘法的三个新算法.
  • 实现了连续时间马尔科夫链模型的算法,专注于氨基酸和密码子模型.
  • 在开源的BEAGLE库 (v4.0.0) 中集成算法.

主要成果:

  • 与现有的GPU算法相比,氨基酸和密码子模型的性能提高了2到3倍.
  • 证明了能源使用量减少了2倍,有助于在进化计算中降低碳足迹.
  • 通过BEAGLE v4.0.0.0 版本向公众提供算法.

结论:

  • 新的算法显著提高了在GPU上的基因推理的速度和能源效率.
  • 这些进展促进了对病原体进化,人口动态和古代基因组的更深入的了解.
  • 这些算法的开源版本支持进化计算的更广泛的科学社区.