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 Classification System01:24

Microbial Classification System

1.4K
Classification is the process of organizing organisms into hierarchically inclusive groups based on their phenotypic similarities or evolutionary relationships. A species comprises one or more strains, and closely related species are grouped into genera. Genera are further classified into families, families into orders, orders into classes, and so forth, up to the domain level, which is the broadest taxonomic rank derived from a combination of phenotypic and genotypic data.The nomenclature of...
1.4K
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

633
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
633
Microbial Morphologies01:29

Microbial Morphologies

4.6K
Bacterial and archaeal cells exhibit remarkable diversity in shape and structure, critical in their adaptability and functionality. Among bacteria, the most commonly observed shapes include cocci and bacilli. Cocci are spherical and may exist singly or in groupings such as pairs (diplococci), chains (streptococci), clusters (staphylococci), or tetrads. Bacilli, in contrast, are rod-shaped and can also occur as single cells, in pairs, or chains, depending on their environmental and genetic...
4.6K
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

781
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...
781
Gene Regulation in Microbial Communities: Quorum Sensing01:28

Gene Regulation in Microbial Communities: Quorum Sensing

779
Quorum sensing is a mechanism of bacterial communication that enables coordinated gene expression in response to changes in population density. This facilitates collective behaviors that enhance survival, resource acquisition, and ecological adaptation. This process relies on small signaling molecules called autoinducers that accumulate as bacterial populations grow. When a critical threshold concentration of autoinducers is reached, bacterial cells collectively modify gene expression,...
779
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

17.2K
The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
17.2K

You might also read

Related Articles

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

Sort by
Same author

Cross-assay RNA modeling reveals cancer biomarkers.

bioRxiv : the preprint server for biology·2026
Same author

Urban greenspaces harbour distinct plasmid communities enriched in heavy metal resistance and competitive traits in arid soils.

Microbiology (Reading, England)·2026
Same author

On the predictability of progression-free survival in ovarian cancer from NanoString gene expression data.

bioRxiv : the preprint server for biology·2026
Same author

Impacts of targeted grazing, controlled burning, and strip seeding on soil microbial communities.

Ecological applications : a publication of the Ecological Society of America·2026
Same author

Predicting missing links in food webs using stacked models and species traits.

Nature communications·2026
Same author

In Science Journals.

Science (New York, N.Y.)·2025
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: Mar 2, 2026

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

4.9K

Using null models to infer microbial co-occurrence networks.

Nora Connor1, Albert Barberán2, Aaron Clauset1,3,4

  • 1Department of Computer Science, University of Colorado, Boulder, Colorado, United States of America.

Plos One
|May 12, 2017
PubMed
Summary
This summary is machine-generated.

Microbiome research often uses pairwise co-occurrence networks, but these can contain statistical noise. This study introduces null models to reveal true ecological signals, finding three-way interactions are significant in soil microbial communities.

More Related Videos

Compost Microcosms as Microbially Diverse, Natural-like Environments for Microbiome Research in Caenorhabditis elegans
07:19

Compost Microcosms as Microbially Diverse, Natural-like Environments for Microbiome Research in Caenorhabditis elegans

Published on: September 13, 2022

2.8K
High Throughput Co-culture Assays for the Investigation of Microbial Interactions
07:00

High Throughput Co-culture Assays for the Investigation of Microbial Interactions

Published on: October 15, 2019

10.8K

Related Experiment Videos

Last Updated: Mar 2, 2026

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

4.9K
Compost Microcosms as Microbially Diverse, Natural-like Environments for Microbiome Research in Caenorhabditis elegans
07:19

Compost Microcosms as Microbially Diverse, Natural-like Environments for Microbiome Research in Caenorhabditis elegans

Published on: September 13, 2022

2.8K
High Throughput Co-culture Assays for the Investigation of Microbial Interactions
07:00

High Throughput Co-culture Assays for the Investigation of Microbial Interactions

Published on: October 15, 2019

10.8K

Area of Science:

  • Microbial ecology
  • Bioinformatics
  • Network analysis

Background:

  • Microbial communities are vital but their interaction networks are poorly understood.
  • Pairwise co-occurrence networks are commonly used to infer ecological interactions.
  • Existing methods for network construction can introduce spurious patterns, obscuring true ecological signals.

Purpose of the Study:

  • To address the problem of statistical noise in microbial interaction networks.
  • To develop and apply a method using null models to distinguish ecological signals from noise.
  • To re-evaluate patterns in a soil microbiome dataset using the improved methodology.

Main Methods:

  • Statistical analysis of operational taxonomic unit (OTU) abundance matrices.
  • Development and application of null models to identify significant pairwise and multi-way interactions.
  • Network analysis of a large soil microbiome dataset.

Main Results:

  • Many previously reported patterns in soil microbiome data were identified as statistical artifacts.
  • The frequency of three-way interactions among microbial OTUs was found to be highly statistically significant.
  • Null models effectively distinguished ecological signals from statistical noise in the analyzed data.

Conclusions:

  • Appropriate null models are crucial for accurate analysis of observational microbiome data.
  • Focusing on three-way interactions offers a promising avenue for understanding microbial ecosystem structure and function.
  • This approach refines our understanding of microbial community ecology and interaction networks.