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

Optimal search-based gene subset selection for gene array cancer classification.

Jiexun Li1, Hua Su, Hsinchun Chen

  • 1Artificial Intelligence Laboratory, Department of Management Information Systems, Eller College of Management, University of Arizona, Tucson, AZ 85721, USA. jiexun@eller.arizona.edu

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society
|August 7, 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

Author Correction: Collagenolysis-dependent DDR1 signalling dictates pancreatic cancer outcome.

Nature·2025
Same author

<i>En-Bloc</i> Kidney Transplantation From Extremely Low-Weight (0.9-5.0 kg) Pediatric Donors: A Decade of Single-Center Experience.

Transplant international : official journal of the European Society for Organ Transplantation·2025
Same author

Inheritance of extraordinary metabolic activity from parental bacteria individuals.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Degradable Metal-Small Molecule Drug Coordination Nanomedicines for DNA Damage-Augmented Cancer Chemodynamic Therapy.

Small (Weinheim an der Bergstrasse, Germany)·2025
Same author

Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study.

The Lancet. Digital health·2025
Same author

Asymmetric Magnetization Switching and All-Electric Field-Free Programmable Spin Logic Enabled by the Interlayer Dzyaloshinskii-Moriya Interaction.

ACS applied materials & interfaces·2025
Same journal

Categorization and segmentation of intestinal content frames for wireless capsule endoscopy.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

An intelligent scoring system and its application to cardiac arrest prediction.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

Guest editorial: Multimedia services and technologies for e-health (MUST-EH).

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

Editorial: From “information technology in biomedicine” to “biomedical and health informatics”.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

Equipment location in hospitals using RFID-based positioning system.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

Distributed system for cognitive stimulation over interactive TV.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2012
See all related articles

Identifying cancer marker genes is crucial for diagnosis. This study introduces tabu search (TS) for optimal gene subset selection from high-dimensional gene array data, proving effective for cancer classification.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High dimensionality in gene expression data poses challenges for accurate cancer classification.
  • Identifying reliable marker genes is essential for developing effective diagnostic tools.

Purpose of the Study:

  • To introduce and evaluate tabu search (TS) as a novel method for optimal gene subset selection.
  • To enhance cancer classification accuracy using high-dimensional gene array data.

Main Methods:

  • Developed a framework incorporating optimal search-based gene selection methods.
  • Applied tabu search (TS) for the first time to gene selection in high-dimensional gene array data.
  • Evaluated group performance of genes to pinpoint globally optimal marker gene sets.

Related Experiment Videos

Main Results:

  • Optimal search-based gene subset selection effectively identifies cancer marker genes.
  • Tabu search (TS) demonstrated significant promise as a tool for gene subset selection.
  • Comparative analysis confirmed the effectiveness of the proposed approach.

Conclusions:

  • Tabu search is a viable and effective method for identifying marker genes in high-dimensional cancer data.
  • Optimal search-based methods provide a robust approach for cancer classification.
  • This work advances the field of gene selection for cancer diagnostics.