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

The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze

Da Wei Huang1, Brad T Sherman, Qina Tan

  • 1Laboratory of Immunopathogenesis and Bioinformatics, Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, MD 21702, USA.

Genome Biology
|September 6, 2007
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

Comparing risk factors in severe COVID-19 using machine learning and non-machine learning methods: analysis from 2 international randomized controlled trials.

JAMIA open·2026
Same author

Five-year immunogenicity and safety follow-up of the PREVAC randomized Trial of Vaccines for Zaire Ebola Virus Disease.

medRxiv : the preprint server for health sciences·2026
Same author

Neurological Manifestations in Adult Survivors of Ebola Virus Disease.

JAMA neurology·2026
Same author

Pathogenesis of diffuse large B cell lymphoma proteogenotypes.

Cancer cell·2026
Same author

MVA-BN monkeypox vaccine safety in a clinical trial in the Democratic Republic of the Congo.

NPJ vaccines·2026
Same author

Prognostic Value of Lung Injury Biomarkers in Patients Hospitalized With COVID-19 Without Respiratory Failure at Admission.

Critical care medicine·2026
This summary is machine-generated.

The DAVID Gene Functional Classification Tool organizes gene lists into biological modules using a novel algorithm. This method aids in interpreting complex gene interactions within a network context.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Gene expression studies generate large datasets requiring interpretation.
  • Understanding functional relationships between genes is crucial for biological research.
  • Existing methods for gene list analysis can be complex and time-consuming.

Purpose of the Study:

  • To introduce the DAVID Gene Functional Classification Tool.
  • To describe its novel agglomeration algorithm for organizing gene data.
  • To facilitate efficient interpretation of gene lists in a network context.

Main Methods:

  • Utilizes a novel agglomeration algorithm.
  • Mines complex biological co-occurrences from multiple functional annotation sources.

Related Experiment Videos

  • Groups functionally related genes and terms into biological modules.
  • Main Results:

    • Condenses extensive gene lists into organized classes.
    • Creates manageable biological modules for easier interpretation.
    • Facilitates understanding of gene function and biological pathways.

    Conclusions:

    • The DAVID tool provides a powerful method for gene list interpretation.
    • Biological module organization enhances understanding of gene networks.
    • It simplifies the analysis of complex functional genomics data.