Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

An efficient algorithm for extracting appliance-time association using smart meter data.

Heliyon·2019

Same journal

Causal intervention validation of gene regulatory signals in scGPT.

Journal of biomedical informatics·2026

Same journal

CoAff-DTI: Fine-grained drug-target interaction prediction using pre-trained language models and affinity-guided mechanisms.

Journal of biomedical informatics·2026

Same journal

Evaluation of temporal preservation in synthetic longitudinal patient data.

Journal of biomedical informatics·2026

Same journal

ARKE: An ontology-driven framework for automated mapping of local radiology procedure terms to the LOINC-RadLex playbook using large language model.

Journal of biomedical informatics·2026

Same journal

A validation-driven training controller for cross-lingual biomedical NER via reinforcement learning-based adaptive loss weighting.

Journal of biomedical informatics·2026

Same journal

ASP-HR: An Adaptive Spatial Perception and Hierarchical Reasoning mechanism for document-level biomedical relation extraction.

Journal of biomedical informatics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Nov 9, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Classification of breast cancer using microarray gene expression data: A survey.

Muhammed Abd-Elnaby¹, Marco Alfonse¹, Mohamed Roushdy²

¹Faculty of Computers and Information Science, Ain Shams University, Cairo, Egypt.

Journal of Biomedical Informatics

|April 8, 2021

Summary

This summary is machine-generated.

This review highlights feature selection techniques for microarray data to improve breast cancer diagnosis. Selecting relevant genes enhances the accuracy of cancer classification from gene expression data.

Keywords:

Cancer classification Feature selection Machine learning Microarray data

More Related Videos

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Published on: August 1, 2018

Clinicopathological Analysis of miRNA Expression in Breast Cancer Tissues by Using miRNA In Situ Hybridization

Clinicopathological Analysis of miRNA Expression in Breast Cancer Tissues by Using miRNA In Situ Hybridization

Published on: June 7, 2016

Related Experiment Videos

Last Updated: Nov 9, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Published on: August 1, 2018

Clinicopathological Analysis of miRNA Expression in Breast Cancer Tissues by Using miRNA In Situ Hybridization

Clinicopathological Analysis of miRNA Expression in Breast Cancer Tissues by Using miRNA In Situ Hybridization

Published on: June 7, 2016

Area of Science:

Biomedical Informatics
Genomics
Cancer Research

Background:

Breast cancer is a leading cause of death globally.
Accurate and early cancer diagnosis is crucial for improving patient outcomes.
Microarray technology offers high-throughput gene expression analysis.

Purpose of the Study:

To review feature selection and classification techniques for microarray data in cancer diagnosis.
To address the challenge of irrelevant or redundant genes in high-dimensional microarray datasets.
To enhance the accuracy of breast cancer classification using gene expression profiles.

Main Methods:

Literature review of feature selection methods.
Analysis of classification techniques applied to microarray data.
Focus on techniques relevant to cancer, specifically breast cancer.

Main Results:

Feature selection is essential for effective microarray-based cancer classification.
Numerous feature selection and classification methods exist in the literature.
The choice of technique impacts the accuracy of diagnostic models.

Conclusions:

Feature selection is a critical preprocessing step for microarray data analysis in cancer research.
Reviewing these techniques aids in developing more accurate breast cancer diagnostic tools.
Further research can optimize gene selection for improved clinical applications.