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

Differential coexpression analysis using microarray data and its application to human cancer.

Jung Kyoon Choi1, Ungsik Yu, Ook Joon Yoo

  • 1National Genome Information Center, Korea Research Institute of Bioscience and Biotechnology, 52 Ueun-dong, Yuseong-gu, Daejeon, Korea.

Bioinformatics (Oxford, England)
|October 20, 2005
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

Comprehensive characterization of the inflammatory ecosystems in immunotherapy-induced adverse events versus chronic inflammatory diseases.

Journal for immunotherapy of cancer·2026
Same author

Improved image reconstruction in coherent diffraction imaging using self-seeded XFEL pulses.

Journal of synchrotron radiation·2026
Same author

Predicting 10-Year Diabetes Risk Through Physiological Acceleration: A Longitudinal Deep Learning Ensemble Approach.

Diagnostics (Basel, Switzerland)·2026
Same author

Programmable Phase Selection between Altermagnetic and Noncentrosymmetric Polymorphs of MnTe on InP via Molecular Beam Epitaxy.

ACS applied materials & interfaces·2026
Same author

B cell-reactive neoantigens boost antitumor immunity.

Science advances·2025
Same author

Surface-plasmon control of ultrafast energy-relaxation modes in photoexcited Au nanorods probed by time-resolved single-particle X-ray imaging.

Nature communications·2025
Same journal

Probabilistic RNA designability via interpretable ensemble approximation and dynamic decomposition.

Bioinformatics (Oxford, England)·2026
Same journal

Quantifying domain-specific relevance of computational biology Wikipedia articles using TF-IDF and cosine similarity.

Bioinformatics (Oxford, England)·2026
Same journal

GATSBI: improving context-aware protein embeddings through biologically motivated data splits.

Bioinformatics (Oxford, England)·2026
Same journal

BiMba: using Vision Mamba to predict protein sites that bind other proteins.

Bioinformatics (Oxford, England)·2026
Same journal

ProMeta: a meta-learning framework for robust disease diagnosis and prediction from plasma proteomics.

Bioinformatics (Oxford, England)·2026
Same journal

Is a Win-Win possible? Achieving pareto-optimal privacy-utility balance in fine-tuned genome language model embeddings against embedding reconstruction attacks.

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

This study introduces a novel model to detect differential gene coexpression in cancer using microarrays. The findings reveal significant alterations in gene networks, impacting cellular functions and potentially tumor progression.

Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Microarrays traditionally identify differential gene expression and coexpressed gene clusters.
  • Alterations in gene coexpression relationships have not been extensively studied.
  • This research addresses the gap by modeling differential coexpression.

Purpose of the Study:

  • To introduce a computational model for identifying differential gene coexpression from microarray data.
  • To assess the biological validity of this model in the context of cancer.

Main Methods:

  • Collected 10 published cancer gene expression datasets across 13 tissues.
  • Constructed separate coexpression networks for tumor and normal tissues.
  • Compared tumor and normal networks to identify altered coexpression relationships.

Related Experiment Videos

Main Results:

  • Cancer significantly alters gene coexpression networks, affecting energy metabolism, cell growth, and immune activity.
  • Identified coregulation of collagen genes linked to invasion and metastasis.
  • Discovered gene clusters related to ribosomal protein synthesis, cell cycle, and antigen presentation in tumor networks.
  • Observed clustered metallothionein expression, potentially involved in apoptosis control.

Conclusions:

  • The developed model offers a novel approach to analyzing microarray data beyond differential expression.
  • Differential coexpression analysis provides insights into cancer biology, including invasion and metastasis.
  • This method has broad applicability for analyzing gene expression data in various biological contexts.