Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Microbial Growth Measurement: Direct Methods01:23

Microbial Growth Measurement: Direct Methods

Direct methods for measuring microbial populations in a culture are essential tools in microbiology, providing quantitative data for various applications. Among these, microscopic counts, plate counts, and serial dilution are widely used techniques, each with unique principles and applications.Microscopic CountsMicroscopic counting involves the use of a Petroff-Hausser chamber, a specialized microscope slide with a grid and defined depth. By observing a liquid culture under a microscope,...
Microbial Growth Measurement: Indirect Methods01:27

Microbial Growth Measurement: Indirect Methods

Estimating microbial growth is essential for understanding population dynamics and environmental adaptations. Indirect methods provide valuable insights by measuring parameters such as turbidity, metabolic activity, and biomass, enabling efficient and reproducible assessments.During exponential growth, microbial cells scatter light proportionally to their biomass, a principle used in turbidity measurements. About one million cells per milliliter produce detectable scattering, which a...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Top-down identification of keystone taxa in the microbiome.

Nature communications·2023
Same author

Individualized network analysis reveals a link between the gut microbiome, diet intervention and Gestational Diabetes Mellitus.

PLoS computational biology·2023
Same author

Complexity-stability trade-off in empirical microbial ecosystems.

Nature ecology & evolution·2022
Same author

Age-related loss of gene-to-gene transcriptional coordination among single cells.

Nature metabolism·2020
Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026
Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026
Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026
Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026
Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026
Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Jun 16, 2026

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres
11:09

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres

Published on: October 23, 2011

16.3K

Network impact of a single-time-point microbial sample.

Shir Ezra1, Amir Bashan1

  • 1Physics Department, Bar-Ilan University, Ramat Gan, Israel.

Plos One
|May 30, 2024
PubMed
Summary
This summary is machine-generated.

The network impact method analyzes single microbiome samples to detect health anomalies by examining species interactions. This approach aids in anomaly detection and classification, improving personalized diagnostics.

More Related Videos

ScanLag: High-throughput Quantification of Colony Growth and Lag Time
07:47

ScanLag: High-throughput Quantification of Colony Growth and Lag Time

Published on: July 15, 2014

16.2K
Evaluating the Impact of Hydraulic Fracturing on Streams using Microbial Molecular Signatures
09:11

Evaluating the Impact of Hydraulic Fracturing on Streams using Microbial Molecular Signatures

Published on: April 4, 2021

3.1K

Related Experiment Videos

Last Updated: Jun 16, 2026

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres
11:09

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres

Published on: October 23, 2011

16.3K
ScanLag: High-throughput Quantification of Colony Growth and Lag Time
07:47

ScanLag: High-throughput Quantification of Colony Growth and Lag Time

Published on: July 15, 2014

16.2K
Evaluating the Impact of Hydraulic Fracturing on Streams using Microbial Molecular Signatures
09:11

Evaluating the Impact of Hydraulic Fracturing on Streams using Microbial Molecular Signatures

Published on: April 4, 2021

3.1K

Area of Science:

  • Microbiome research
  • Computational biology
  • Ecological network analysis

Background:

  • The human microbiome significantly impacts health and disease.
  • Microbiome analysis traditionally requires extensive sampling.
  • Individualized microbiome data can reveal host-specific health information.

Purpose of the Study:

  • To introduce and evaluate variations of the network impact approach for single-sample microbiome analysis.
  • To assess the utility of network impact in anomaly detection and classification tasks.
  • To explore the potential of individualized microbiome analysis for clinical applications.

Main Methods:

  • Simulated microbiome samples generated using the Generalized Lotka-Volterra model.
  • Systematic performance evaluation of different network impact variations.
  • Application of network impact for anomaly detection and binary/multiclass classification.

Main Results:

  • The network impact effectively captures inter-species interactions within a single sample.
  • Network impact successfully identifies 'shuffled' samples with normal abundance but abnormal interactions.
  • The method demonstrates efficacy in classifying samples based on interaction profiles.

Conclusions:

  • The network impact method offers a powerful tool for analyzing single-time-point microbiome samples.
  • This approach enhances anomaly detection by focusing on ecological interactions, not just abundance.
  • Individualized microbiome network analysis holds promise for improved diagnostics and personalized medicine.