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 Interactions: Cooperation01:26

Microbial Interactions: Cooperation

Microbial cooperation involves beneficial interactions in which different species work together for individual or mutual advantage. These interactions can profoundly influence ecological dynamics and evolutionary processes, and they are essential to many pathogenic and symbiotic relationships.Nematode–Bacteria CooperationA striking example is the relationship between the Gram-negative bacterium Xenorhabdus nematophila and the parasitic nematode Steinernema carpocapsae. Juvenile nematodes...
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...
Microbial Biosensors01:17

Microbial Biosensors

Microbial biosensors are analytical devices that utilize living microbes to detect specific substances through measurable signals. These devices consist of two main components: biosensing organisms and signal-transducing elements. Biosensing organisms, such as Escherichia coli or Saccharomyces cerevisiae, are typically housed in multiwell plates connected to transducers, enabling rapid, real-time detection of target analytes.Signal Generation MechanismWhen a target analyte—such as...
Global Regulatory Systems01:28

Global Regulatory Systems

Global regulatory systems in bacteria enable rapid and coordinated responses to environmental changes by integrating sensory inputs with gene expression, ensuring efficient adaptation to fluctuating conditions. Key global regulatory mechanisms include regulons, two-component systems, sigma factors, and secondary messengers.Regulons and Global RegulatorsA regulon is a collection of genes and operons controlled by a common global regulator. These regulators enable bacteria to prioritize resource...
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 Microbial Ecology01:28

Introduction to Microbial Ecology

Microbial ecology examines the complex web of interactions and diversity among microorganisms within various ecosystems. This field seeks to understand how microbial populations adapt to and influence their environments and how these interactions shape broader ecological processes. Microbes are integral to ecosystem function, participating in nutrient cycling, energy flow, and the maintenance of environmental homeostasis.An ecosystem represents a dynamic interaction between living organisms...

You might also read

Related Articles

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

Sort by
Same author

Phenome-wide association network demonstrates close connection with individual disease trajectories from the HUNT study.

PloS one·2024
Same author

Author Correction: Predictive evolution of metabolic phenotypes using model-designed environments.

Molecular systems biology·2024
Same author

Highly parallelized laboratory evolution of wine yeasts for enhanced metabolic phenotypes.

Molecular systems biology·2024
Same author

Genome-wide association studies reveal differences in genetic susceptibility between single events vs. recurrent events of atrial fibrillation and myocardial infarction: the HUNT study.

Frontiers in cardiovascular medicine·2024
Same author

Genome-scale metabolic models reveal determinants of phenotypic differences in non-Saccharomyces yeasts.

BMC bioinformatics·2023
Same author

Phage therapy minimally affects the water microbiota in an Atlantic salmon (Salmo salar) rearing system while still preventing infection.

Scientific reports·2023

Related Experiment Video

Updated: May 22, 2026

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Complex network analysis in microbial systems: theory and examples.

Zahra Zavareh1, Eivind Almaas

  • 1Department of Biotechnology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.

Methods in Molecular Biology (Clifton, N.J.)
|May 29, 2012
PubMed
Summary

Systems Biology relies on understanding component interactions. Network analysis reveals patterns in complex biological systems, applied here to protein and metabolic networks.

More Related Videos

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform
09:24

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform

Published on: June 6, 2017

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
09:49

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

Related Experiment Videos

Last Updated: May 22, 2026

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform
09:24

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform

Published on: June 6, 2017

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
09:49

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

Area of Science:

  • Systems Biology
  • Network Science
  • Bioinformatics

Background:

  • Understanding complex biological systems requires analyzing component interactions.
  • Network analysis offers a powerful approach to identify patterns and principles in biological networks.

Purpose of the Study:

  • To describe central network concepts and their algorithmic implementations.
  • To demonstrate the application of network analysis on biological networks.

Main Methods:

  • Detailed description of network theory concepts.
  • Algorithmic implementation of network analysis techniques.
  • Application to a protein-interaction network (Mus musculus) and a genome-scale metabolic network (Yersinia pestis).

Main Results:

  • Illustrates the utility of network analysis in uncovering structural properties of biological networks.
  • Provides a framework for analyzing complex biological interactions.

Conclusions:

  • Network analysis is essential for comprehending biological system functioning.
  • The presented methods are applicable to diverse biological network types.