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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...
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...
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...
Microbiota of the Large Intestine01:27

Microbiota of the Large Intestine

The large intestine hosts the most densely populated microbial ecosystem in the human body. This complex community primarily consists of anaerobic bacteria, with Bacillota (formerly Firmicutes) and Bacteroidota (formerly Bacteroidetes) as the predominant groups. The distribution of these microbes varies along different sections of the large intestine, influenced by local environmental factors such as oxygen availability and nutrient composition.The cecum, located at the beginning of the large...

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相关实验视频

Updated: Jun 11, 2026

An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota
07:15

An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota

Published on: July 31, 2019

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在纵向数据集中微生物组组成的插曲.

Omri Peleg1, Elhanan Borenstein1,2,3

  • 1Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.

mBio
|August 20, 2024
PubMed
概括

对缺少的肠道微生物组数据进行准确的插值对于纵向研究至关重要. K-最近邻近算法显示出有希望的结果,其准确性受到微生物组稳定性和采样频率等因素的影响.

科学领域:

  • 微生物组研究 微生物组研究
  • 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:

  • 对人类肠道微生物群的纵向研究对于了解健康至关重要.
  • 不完整或不规则的抽样在这些研究中带来了重大分析挑战.
  • 现有的微生物组数据插值方法缺乏全面的评估和标准化指导方针.

研究的目的:

  • 严格评估一系列用于纵向微生物群数据的插值方法.
  • 确定最准确,最可靠的技术来推断缺少的微生物组合.
  • 为在未来的研究中插入微生物组数据提供最佳实践指南.

主要方法:

  • 系统地实施和评估各种插值算法.
  • 使用了三个纵向微生物组数据集,并进行了交叉验证.
  • 根据影响因素开发了一个预测模型来估计基于影响因素的插值准确性.

主要成果:

  • K-最近邻近算法证明了跨数据集的卓越插值准确性.
  • 插值准确性因微生物组稳定性,样本大小和时间间隔而有显著差异.
  • 开发了一个预测模型,以预测特定时间点的插值准确性.
关键词:
插值的插值是指一个插值.纵向数据 纵向数据 纵向数据微生物组是一个微生物组.

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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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Visualization of Gut Microbiota-host Interactions via Fluorescence In Situ Hybridization, Lectin Staining, and Imaging
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Visualization of Gut Microbiota-host Interactions via Fluorescence In Situ Hybridization, Lectin Staining, and Imaging

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相关实验视频

Last Updated: Jun 11, 2026

An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota
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An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota

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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

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Visualization of Gut Microbiota-host Interactions via Fluorescence In Situ Hybridization, Lectin Staining, and Imaging
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结论:

  • 纵向微生物组数据的准确插值是可行的,特别是在采样密集的队列中.
  • K-最近邻近方法是微生物组数据归算的一个非常有效的工具.
  • 未来的研究可以利用预测模型来优化数据插值并提高分析可靠性.