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

Gene microarray analysis using angular distribution decomposition.

Karen Lees1, Stephen Roberts, Pari Skamnioti

  • 1Department of Engineering Science, University of Oxford, Oxford, United Kingdom.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|March 27, 2007
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

Fe-oxyhydroxide deposits at Semenov hydrothermal field (13°30'N), Mid-Atlantic ridge: insights into formation, modification and resource potential.

Mineralium deposita·2026
Same author

Co-learning in crisis: A comparative analysis of digital preparedness during COVID-19 in Taiwan and the United Kingdom.

Global public health·2025
Same author

"Fighting against malaria is everyone's concern": a randomized control trial assessing the role of incentives for encouraging local communities to record and upload mosquito sounds using the MozzWear application.

Malaria journal·2025
Same author

Public health disinformation, conflict, and disease outbreaks: a global narrative integrative review to guide new directions for health diplomacy.

Global health action·2025
Same author

Do monetary incentives encourage local communities to collect and upload mosquito sound data using smartphones? A case study in the Democratic Republic of the Congo.

PloS one·2025
Same author

Addressing environmental harms in the health sector: environmentality as a lens to expose (neglected) sites of knowledge/power.

Humanities & social sciences communications·2025
Same journal

GMSA: A Graph Matching and Point Cloud Registration-Based Method for Spatial Transcriptomics Data Alignment.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Investigations on Multiple Protein Scaffold Filling.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised Learning.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

PPIGAN: Prediction of Protein-Protein Interactions Using Generative Adversarial Networks.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Deep Structure-Enhanced Cell Clustering Model for Single-Cell RNA Sequencing Data.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Asymmetric Drug-Drug Interaction Prediction Based on Generative Adversarial Networks and Knowledge Graph.

Journal of computational biology : a journal of computational molecular cell biology·2026
See all related articles

This study introduces a novel method for analyzing gene expression data from microarrays. It uses an angular transformation and pairwise comparisons to effectively cluster genes with similar expression patterns, aiding in the discovery of potential target genes.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Microarray data analysis commonly employs clustering to group genes with similar expression profiles.
  • The effectiveness of clustering is highly dependent on the data transformation methods used.
  • Identifying genes with specific expression patterns is crucial for biological discovery.

Purpose of the Study:

  • To present a new method for gene expression data analysis using relative expression changes and angular transformation.
  • To enable controlled definition of gene similarity based on pairwise condition comparisons.
  • To facilitate the identification of biologically relevant gene clusters and target genes.

Main Methods:

  • Utilizing relative expression changes between experimental conditions.

Related Experiment Videos

  • Applying an angular transformation to gene expression data.
  • Employing variational Bayes mixture modeling for cluster analysis.
  • Developing visualization techniques for expression patterns and intensity changes.

    • Main Results:

    • The angular transformation maps data to a representation suitable for mining relative regulation changes.
    • The method allows automatic mining of expression change information, aiding cluster characterization.
    • Visualization techniques effectively highlight potential target genes within identified clusters.

    Conclusions:

    • The proposed method enhances the analysis of microarray data by providing a robust approach to gene clustering.
    • It improves the ability to identify and locate clusters of genes with specific expression patterns.
    • The technique facilitates the discovery of potential target genes for further experimental investigation.