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相关概念视频

Infection01:20

Infection

7.7K
When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
7.7K

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相关实验视频

Updated: Jun 6, 2025

A Web Tool for Generating High Quality Machine-readable Biological Pathways
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spread.gl:在高性能浏览器应用程序中可视化病原体的传播.

Yimin Li1,2, Nena Bollen1,2, Samuel L Hong1

  • 1Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven 3000, Belgium.

Bioinformatics (Oxford, England)
|December 3, 2024
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概括
此摘要是机器生成的。

我们开发了Spread.gl,这是一个开源应用程序,用于可视化病原体传播历史. 该工具有助于研究人员了解时空传播模式,并探索影响疾病传播的环境因素.

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科学领域:

  • 流行病学 流行病学
  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 贝叶斯哲学地理分析对于了解病原体传播历史至关重要.
  • 解释复杂的植物地理数据需要先进的可视化工具.

研究的目的:

  • 开发一个直观和功能丰富的可视化工具,用于植物地理重建.
  • 为了能够探索影响病原体传播的环境因素.

主要方法:

  • 开发Spread.gl,一个开源的,基于浏览器的应用程序.
  • 对离散和连续的植物地理推理的可视化.
  • 病原体通过时间的地理分散的动画.
  • 植物遗传数据与环境数据层的整合.

主要成果:

  • 斯普雷德.格尔 (Spread.gl) 提供了对植物地理数据的平滑和直观可视化.
  • 该应用程序支持动画病原体随时间的传播.
  • 使用大规模的SARS-CoV-2基因组数据集 (>17000个序列) 证明了实用性.

结论:

  • Spread.gl增强了复杂的植物地理分析的解释.
  • 有助于探索病原体传播的环境驱动因素.
  • 为流行病学研究和公共卫生提供了宝贵的资源.