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

Pathway-based classification of breast cancer subtypes.

Alex Graudenzi1, Claudia Cava2, Gloria Bertoli3

  • 1Institute of Molecular Bioimaging and Physiology of the Italian National Research Council (IBFM-CNR), Milan, Italy, and Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy, alex.graudenzi@unimib.it.

Frontiers in Bioscience (Landmark Edition)
|April 15, 2017
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

Ferroptosis-induced oxidative stress in therapy-resistant glioblastoma.

Cell death discovery·2026
Same author

Hyperspectral imaging and healthy aging: an observational study using hand skin as surface for monitoring healthy aging processes.

Biogerontology·2026
Same author

Advancing Brain Tumor Diagnosis Using Deep Learning: A Systematic and Critical Review on Methodological Approaches to Glioma Segmentation and Classification Through Multiparametric MRI.

Brain sciences·2026
Same author

Prognostic Score for Myelodysplastic Syndromes Based on Molecular Evolution.

NEJM evidence·2026
Same author

<i>In silico</i> profiling of date palm pollen phytochemicals: Molecular interactions with sperm-associated proteins and implications for male fertility.

Nutrition and health·2026
Same author

Maternal-fetal microRNA axis in congenital heart disease: implications for tetralogy of Fallot.

Frontiers in cardiovascular medicine·2026

This study introduces a novel computational tool to classify cancer subtypes using gene expression data. The method maintains high accuracy even with reduced data, aiding precision medicine in cancer diagnostics.

Area of Science:

  • Computational biology
  • Genomics
  • Precision medicine

Background:

  • Cancer heterogeneity complicates personalized theranostic strategies.
  • Genomic data analysis offers tools for decision support in oncology.
  • Precision medicine requires accurate patient and tumor profiling.

Purpose of the Study:

  • To develop a novel computational classifier for cancer subtypes using gene expression data.
  • To apply the classifier to breast cancer datasets for validation.
  • To assess the classifier's performance with reduced variable spaces.

Main Methods:

  • Support Vector Machines (SVM) algorithm.
  • Utilizing relevant pathway information to reduce variable space.
  • Application to TCGA and GEO breast cancer datasets.

Related Experiment Videos

Main Results:

  • The novel classifier accurately identifies cancer subtypes.
  • High accuracy was maintained even with a 20-fold reduction in variable space.
  • The tool provides effective cancer patient profiling.

Conclusions:

  • The developed computational classifier is a valuable tool for cancer subtype classification.
  • The method offers efficient patient profiling with reduced experimental resources.
  • This approach supports precision medicine by addressing cancer heterogeneity.