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相关概念视频

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Updated: Jul 19, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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使用概率图和外部知识集成元多态数据的集成.

Handan Can1, Sree K Chanumolu1, Barbara D Nielsen2

  • 1Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.

Cells
|August 11, 2023
PubMed
概括
此摘要是机器生成的。

我们开发了一个新的算法来分析来自细菌群落的多omics数据. 这种方法揭示了复杂的相互作用,为微生物适应和功能提供了洞察力,而不是单一的omics方法.

关键词:
贝叶斯网络是一个贝叶斯网络.乳酸菌克菲拉诺法奇纳斯 (Lactobacillus kefiranofaciens) 是一种兰氏杆菌克菲里 (Lentilactobacillus kefiri) 是一种植物.克菲尔 (kefir) 是一种葡萄酒.多种主题的多种主题.

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科学领域:

  • 微生物学 微生物学
  • 系统生物学 系统生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 多学科数据提供了对生物系统的全面了解,但分析方法尚未得到充分发展.
  • 凯菲尔谷物拥有稳定的微生物群落,具有已知的健康益处.
  • 了解微生物相互作用是利用其潜力的关键.

研究的目的:

  • 开发和应用一种新的算法来分析来自细菌群体的多omics数据.
  • 在不同的温度下为*Lentilactobacillus kefiri*和*Lactobacillus kefiranofaciens*构建一个多样化的相互作用网络.
  • 了解微生物适应和社区动态.

主要方法:

  • 开发了一种使用概率图表表示和外部知识进行最佳结构学习的新算法.
  • 从30°C和37°C的*L. kefiri*和*L. kefiranofaciens*的受控共培养中收集了转录组,代谢组和蛋白组数据.
  • 从20个样本构建了一个多omics交互网络.

主要成果:

  • 多omics网络提供了超越单个omics分析的见解.
  • 鉴定了转录物,蛋白质和代谢物之间的相互作用,表明活性毒素/抗毒素系统.
  • 观察到涉及shikimate通路的复杂相互作用,解释了37°C的细菌适应,协聚和*L. kefiranofaciens*的差异激活.

结论:

  • 开发的算法有效地从多omics数据中重建复杂的微生物相互作用网络.
  • 该研究阐明了细菌适应温度压力和社区相互作用的基础分子机制.
  • 这种方法增强了我们对微生物群落的理解,比如在里发现的微生物群落.