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 Video

Updated: Jul 18, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Classification methods for the development of genomic signatures from high-dimensional data.

Hojin Moon1, Hongshik Ahn, Ralph L Kodell

  • 1Division of Biometry and Risk Assessment, National Center for Toxicological Research, FDA, NCTR Road, Jefferson, AR 72079, USA. hojin.moon@fda.hhs.gov

Genome Biology
|December 22, 2006
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

Authors' Reply: Posttrial Withdrawal Ethics in the Healthy Ageing Ecosystem for People With Dementia (HAAL) Study.

JMIR research protocols·2026
Same author

Coordinated Temporal Dynamics of Glucocorticoid Receptor Binding and Chromatin Landscape Drive Transcriptional Regulation.

bioRxiv : the preprint server for biology·2026
Same author

Damping behavior of adaptable shoe under torsional loading at varying angular velocities: replicating the effects on cutting maneuvers.

Scientific reports·2026
Same author

Melatonin-Loaded Sacchachitin Nanofiber Hydrogel as a Novel Non-Steroidal Platform for Atopic Dermatitis Therapy.

International journal of nanomedicine·2026
Same author

Comparison of multi-planar and sagittal-plane stepping machines for walking and balance restoration in chronic stroke: a randomized control trial (RCT).

Scientific reports·2026
Same author

Linker histone H1.5 contributes to centromere integrity.

Nucleic acids research·2026

Classification by Ensembles from Random Partitions (CERP) accurately predicts patient outcomes using genomic data. Combining clinical information with genomic data further enhances predictive accuracy for personalized medicine.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Personalized medicine leverages patient genomic signatures for targeted therapy selection.
  • Accurate classification algorithms are crucial for interpreting complex genomic data in clinical settings.

Purpose of the Study:

  • To introduce and evaluate the Classification by Ensembles from Random Partitions (CERP) algorithm for class prediction.
  • To assess CERP's performance on leukemia and breast cancer genomic datasets.

Main Methods:

  • Application of the CERP algorithm for classification tasks.
  • Comparative analysis of CERP against other classification algorithms using genomic and clinical datasets.

Main Results:

  • CERP demonstrates consistent and strong performance across different datasets.

More Related Videos

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Related Experiment Videos

Last Updated: Jul 18, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

  • Integration of clinical/histopathological data with genomic data significantly improves predictive accuracy.

    • Conclusions:

    • CERP is a robust and effective tool for genomic data classification in personalized medicine.
    • Combining diverse data types, including clinical variables, enhances the precision of therapeutic assignment.