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相关概念视频

Methods to Assess Microbial Communities01:19

Methods to Assess Microbial Communities

Microbial communities, comprising bacteria, archaea, and eukaryotic microorganisms, inhabit diverse ecosystems and play crucial roles in environmental and biological processes. Their diversity is defined by three main parameters: species richness (the number of distinct species), species abundance (the relative quantity of each species), and species evenness (how uniformly individual species are distributed in various locations). These factors together shape the structure and ecological balance...
Methods to Assess Microbial Populations01:30

Methods to Assess Microbial Populations

Assessing microbial populations is crucial for understanding microbial roles in health, ecology, and industry. Various complementary techniques—both culture-based and molecular—enable detailed analysis of microbial abundance, diversity, and function.Viable Plate CountThe viable plate count is a traditional culture-based method used to estimate the number of living microbes in a sample. After serial dilution, the sample is spread onto nutrient agar plates. Each viable cell forms a visible...
Introduction to the Human Microbiota01:22

Introduction to the Human Microbiota

Microorganisms colonize various regions of the human body, including the mouth, nasal passages, throat, stomach, intestines, urogenital tract, and skin. The total number of microbial cells is estimated to range from 10¹³ to 10¹⁴—comparable to, or exceeding, the number of human somatic cells. This host–microbiome relationship has led to the conceptualization of humans as supraorganisms, wherein microbial communities perform vital roles in development, immunity, and disease...
Development of Human Microbiota01:30

Development of Human Microbiota

The human microbiota begins developing at birth and undergoes continual change as we age. Infancy marks a critical period of microbial sensitivity, offering a “window of opportunity” during which beneficial microbes help mature the immune system. By age three, children typically develop a more stable and diverse microbial community. Newborns acquire microbes from their immediate environment; vaginal delivery favors maternal vaginal microbes, while cesarean births favor microbes from the skin...

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相关实验视频

Updated: Jun 15, 2026

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
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parafac4microbiome:使用并行因子分析对纵向微生物组数据的探索性分析.

G R van der Ploeg1, J A Westerhuis1, A Heintz-Buschart1

  • 1Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands.

mSystems
|May 21, 2025
PubMed
概括
此摘要是机器生成的。

平行因子分析 (PARAFAC) 有效地分析了纵向微生物群数据,揭示了传统方法错过的时间动态. 这种方法增强了比较研究,并识别了微生物转移,即使缺少数据,并且可以在R包中获得.

关键词:
帕拉法卡 (PARAFACAC) 是一个分解,分解,分解.动力学 动力学 动力学多通道的多通道张数分解因子化方式

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科学领域:

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

背景情况:

  • 纵向微生物组研究产生复杂的多维数据.
  • 传统的方法,如主要组件分析,往往无法有效地捕捉时间动态.
  • 多路分析方法为结构化微生物组数据提供了更合适的框架.

研究的目的:

  • 为了证明平行因子分析 (PARAFAC) 对于探索纵向微生物组数据的有用性.
  • 展示PARAFAC识别时间模式和结构变化的能力.
  • 为应用PARAFAC在微生物组研究中提供一个可访问的R包.

主要方法:

  • 将并行因子分析 (PARAFAC) 应用于三个不同的纵向微生物群数据集.
  • 数据以三向阵列形式组织:受试者,微生物丰度和时间点.
  • 为微生物子群体的识别而应用的后期聚类.

主要成果:

  • 在一项体外微生物组研究中,PARAFAC成功地确定了初级时间解析变异.
  • 该方法区分了受试者群体,并改善了婴儿肠道微生物组纵向研究中的比较分析,即使缺少数据.
  • 在口腔微生物组的牙周炎干预研究中,PARAFAC促进了微生物子社区的识别.

结论:

  • 平行因子分析 (PARAFAC) 是一种强大而通用的方法,用于在各种环境中分析纵向微生物群数据.
  • 该方法有效地捕捉时间和结构模式,优于传统方法.
  • 该parafac4microbiome R包为研究人员提供了可访问的工具,以便他们在自己的研究中应用PARAFAC.