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

INCLUSive: integrated clustering, upstream sequence retrieval and motif sampling.

Gert Thijs1, Yves Moreau, Frank De Smet

  • 1ESAT_ SISTA/COSIC, KULeuven, Kasteelpark Arenberg 10, 3001 Leuven-Heverlee, Belgium. Gert.Thijs@esat.kuleuven.ac.be

Bioinformatics (Oxford, England)
|February 16, 2002
PubMed
Summary

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

OGTFinder: A Curated Growth Temperature Data Set and Its Application To Predict Optimal Growth Temperatures of Bacteria and Archaea.

Journal of chemical information and modeling·2026
Same author

Simplified mechanical organs in aquatic plants are associated with the loss of expansin genes.

Plant physiology·2026
Same author

Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer.

Genome medicine·2026
Same author

Filtering for truth: high-precision taxonomic classification in nanopore shotgun metagenomics data through a KMA-based bioinformatic pipeline (KAPTAIN).

BMC genomics·2026
Same author

Recovery and microbial host assignment of mobile genetic elements in complex microbiomes: insights from a spiked gut sample.

mSystems·2026
Same author

ADNEX-AI: automated extraction of ultrasound predictors for interpretable ovarian cancer risk stratification.

NPJ precision oncology·2025

INCLUSive automates microarray data analysis, performing gene clustering and motif discovery. This tool identifies co-expressed genes and their regulatory elements, streamlining biological insights.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Microarray analysis is crucial for understanding gene expression patterns.
  • Identifying regulatory motifs in co-expressed genes aids in deciphering gene regulation.
  • Automating these complex analyses can significantly accelerate biological discovery.

Purpose of the Study:

  • To introduce INCLUSive, a novel software tool for automated multistep analysis of microarray data.
  • To enable efficient clustering of genes based on expression profiles and subsequent motif finding in their regulatory regions.

Main Methods:

  • Utilizes adaptive quality-based clustering to group genes with similar expression profiles.
  • Integrates with GenBank to retrieve upstream sequences of clustered genes.

Related Experiment Videos

  • Employs Motif Sampler, a Gibbs sampling algorithm, for statistically identifying over-represented motifs in gene upstream sequences.

    • Main Results:

    • Demonstrates INCLUSive's capability for automated, sequential analysis of microarray data.
    • Successfully clusters genes and identifies statistically significant motifs in the upstream regions of co-expressed genes.
    • Provides a streamlined workflow for exploring potential gene regulatory mechanisms.

    Conclusions:

    • INCLUSive offers an automated and efficient approach to microarray data analysis, combining gene clustering and motif discovery.
    • Facilitates the identification of regulatory elements associated with co-expressed genes, advancing the study of gene regulation.
    • This tool has the potential to accelerate research in genomics and systems biology.