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 Experiment Videos

Microbial genotype-phenotype mapping by class association rule mining.

Makio Tamura1, Patrik D'haeseleer

  • 1Lawrence Livermore National Laboratory, Computing Applications and Research Department/Chemistry, Materials, Earth and Life Sciences Department, Microbial Systems Biology Group, Livermore, CA 94550, USA. makio323@gmail.com

Bioinformatics (Oxford, England)
|May 10, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

The distinct trimeric structure of the immunodominant chlamydial antigen Major Outer Membrane Protein.

Nature communications·2026
Same author

Identification of Bacterial Networks and Relationship to Host Responses in Early Periodontitis Population over 24 Months.

International journal of molecular sciences·2025
Same author

Transporter annotations are holding up progress in metabolic modeling.

Frontiers in systems biology·2025
Same author

Galactomyces ferment filtrate upregulates anchoring junctions and stabilizes actin to maintain the Young's modulus of skin cells in vitro.

International journal of cosmetic science·2025
Same author

Sequence, structure prediction, and epitope analysis of the polymorphic membrane protein family in Chlamydia trachomatis.

PloS one·2024
Same author

The Polymorphic Membrane Protein G Has a Neutral Effect and the Plasmid Glycoprotein 3 an Antagonistic Effect on the Ability of the Major Outer Membrane Protein to Elicit Protective Immune Responses against a <i>Chlamydia muridarum</i> Respiratory Challenge.

Vaccines·2023
Same journal

3DICE: Interpretable 3D Cross-Modal Learning for Drug-Target Interaction Prediction and Large-Scale Drug Discovery.

Bioinformatics (Oxford, England)·2026
Same journal

KASSPer: Kinase Active Site Structure Prediction using Protein and Ligand Language Models and Its Application to Virtual Screening.

Bioinformatics (Oxford, England)·2026
Same journal

IDR searcher: a search engine solution for public image resources.

Bioinformatics (Oxford, England)·2026
Same journal

KCFtools: Rapid alignment-free method for introgression screening and GWAS using k-mer profiles.

Bioinformatics (Oxford, England)·2026
Same journal

Meta2DB: Curated shotgun metagenomic feature sets and metadata for health state prediction.

Bioinformatics (Oxford, England)·2026
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
See all related articles

This study introduces netCAR, an algorithm for identifying sets of genes associated with microbial phenotypes. netCAR efficiently extracts multiple-to-one gene associations, revealing complex biological networks and outperforming previous methods.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Microbial Genomics

Background:

  • Microbial phenotypes arise from complex gene interactions, not single genes.
  • Traditional methods often miss these multi-gene associations.
  • A new approach is needed to analyze sets of genes linked to phenotypes.

Purpose of the Study:

  • To develop an efficient algorithm, netCAR, for mining sets of Clusters of Orthologous Groups (COGs) associated with microbial phenotypes.
  • To analyze multiple-to-one (set-to-phenotype) associations rather than pairwise (gene-to-phenotype) relationships.
  • To leverage phylogenetic co-occurrence graphs and mutual information for robust association rule mining.

Main Methods:

  • Developed netCAR, a novel class association rule mining algorithm.

Related Experiment Videos

  • Utilized COG phylogenetic profiles and phenotype profiles from 155 prokaryotic organisms.
  • Incorporated phylogenetic co-occurrence graphs to reduce the search space.
  • Employed mutual information to assess biconditional relationships between COG sets and phenotypes.

    • Main Results:

    • netCAR identified approximately 10 times more relevant COGs for six microbial phenotypes using multiple-to-one association compared to one-to-one.
    • Revealed distinct network topologies (modules) of COG associations for different phenotypes (e.g., motility, aerobic).
    • netCAR demonstrated superior performance and significantly reduced computational time compared to the CARapriori algorithm for extracting 3-COG sets.

    Conclusions:

    • Multiple-to-one association rule mining is more effective for uncovering gene-phenotype relationships in microbes.
    • netCAR provides an efficient and powerful tool for discovering complex microbial functional networks.
    • The findings offer insights into the genetic architecture underlying diverse microbial phenotypes.