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相关概念视频

Environmental Applications of Microorganisms01:30

Environmental Applications of Microorganisms

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Microorganisms play a pivotal role in maintaining ecosystem balance by recycling essential elements such as carbon, nitrogen, and phosphorus, as well as supporting processes like bioremediation, wastewater treatment, and biofuel production.Microbes in Elemental CyclesIn the carbon cycle, microorganisms decompose organic matter, releasing carbon dioxide via aerobic respiration. This carbon dioxide is subsequently used by photosynthetic organisms to synthesize organic compounds, closing the...
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Updated: Sep 12, 2025

Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands
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预测城市废水微生物组动态使用数字双胞胎框架.

Bichar Dip Shrestha Gurung1, Manish Rayamajhi1, Naina Maharjan2

  • 1University of South Dakota, Department of Biomedical Engineering, Sioux Falls, 57107, USA.

bioRxiv : the preprint server for biology
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PubMed
概括

我们开发了一个数字双胞胎框架,Q-net,用于预测城市废水中的微生物变化. 这个模型准确地预测了微生物的丰富性,推动了废水微生物组研究从描述性到预测性.

关键词:
数字双胞胎 数字双胞胎 数字双胞胎一个MAG就是MAG,MAG就是MAG.转基因组学是指转基因组学.微生物的丰富性 微生物的丰富性预测建模的预测建模.这就是Q-net.时间序列预测时间序列预测废水中的微生物组

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科学领域:

  • 环境微生物学环境微生物学
  • 计算生物学是一种计算生物学.
  • 系统生态学 系统生态学

背景情况:

  • 城市废水是复杂的微生物群落的港口,为公众健康提供了洞察力.
  • 目前的废水微生物组研究主要是描述性的,缺乏预测能力.
  • 预测建模对于理解微生物动态和公共卫生趋势至关重要.

研究的目的:

  • 引入一个数字双胞胎框架 (Q-net) 来预测城市废水中的微生物丰富性.
  • 为废水微生物组分析开发一个可解释的生成模型.
  • 为了能够在各种场景下模拟微生物趋势.

主要方法:

  • 利用了来自七个废水处理厂的30周纵向元基因组数据集.
  • 开发和训练了一种可解释的生成模型,Q-net,用于微生物丰度预测.
  • 为了模型的透明度和可解释性,采用了条件推理树.

主要成果:

  • Q-net实现了时间微生物动态的高准确性预测 (关键种类的R2>0.97).
  • 该模型在最后一个时间点 (R2 = 0.998) 显示出非常高的准确性.
  • 在假设场景下,Q-net成功模拟了现实的微生物趋势.

结论:

  • 像Q-net这样的数字双胞胎可以将废水微生物组研究转化为动态的预测系统.
  • 这种方法对环境监测和微生物生态系统建模具有重大影响.
  • Q-net的可解释性增强了对废水微生物生态学的理解.