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

Search research articles

Related Experiment Video

Updated: Feb 25, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Gene selection for tumor classification using a novel bio-inspired multi-objective approach.

M Dashtban¹, Mohammadali Balafar¹, Prashanth Suravajhala²

¹Department of Computer Engineering, Faculty of Electrical & Computer Engineering, University of Tabriz, Iran.

|August 7, 2017

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

In silico approaches to improved understanding of herbicides targeting photosystem II (PSII).

Computational biology and chemistry·2026

Same author

Toward the genetic landscape of prostate cancer in India: insights from whole-exome and low-pass whole-genome sequencing of formalin-fixed paraffin-embedded tumor tissues.

Frontiers in systems biology·2026

Same author

Integrating multi-omics data for next-generation cancer research and precision medicine.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico·2026

Same author

Draft genome sequencing of Proteus mirabilis strain Indica (ST286) reveals antimicrobial resistance and virulence determinants.

BMC microbiology·2026

Same author

Distinct genetic variants from the whole-exome sequencing of syndromic anorectal malformations: A cross-sectional study.

iScience·2026

Same author

Isolation and genomic characterization of a lytic bacteriophage against multidrug-resistant Proteus mirabilis.

Applied microbiology and biotechnology·2026

This study introduces a novel bio-inspired algorithm for selecting informative genes in cancer microarray data. The method enhances gene selection accuracy, aiding in the discovery of potential cancer biomarkers.

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Gene selection is crucial for microarray data analysis, but cancer datasets present significant challenges.
Identifying informative genes aids in understanding complex diseases and developing targeted therapies.

Purpose of the Study:

To propose a novel bio-inspired multi-objective algorithm for gene selection in binary microarray data classification.
To enhance the accuracy and effectiveness of identifying significant biomarkers for cancer genomic analysis.

Main Methods:

A novel Bio-inspired Multi-objective algorithm extending the Bat Algorithm with refined formulations and social learning concepts.
Integration of multi-objective operators and novel local search strategies for random walks.
Application of a hybrid model incorporating the Fisher criterion to cancer microarray datasets.

Keywords:

Bat algorithm Cancer classification Evolutionary algorithms Feature selection Gene selection Microarray data analysis

More Related Videos

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Published on: August 25, 2023

Related Experiment Videos

Last Updated: Feb 25, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens

Published on: August 25, 2023

Main Results:

The proposed algorithm effectively identifies informative genes and novel combinations of biomarkers.
Experimental results demonstrate the method's effectiveness on widely-used microarray cancer datasets.
Identified biomarkers show associations with existing research findings.

Conclusions:

The developed algorithm offers a powerful tool for genomic analysis and biomarker discovery in cancer research.
This approach advances gene selection techniques for complex biological data.
The findings contribute to a better understanding of cancer through informative gene identification.