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Related Experiment Video

Updated: Feb 1, 2026

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Identification of tissue-specific tumor biomarker using different optimization algorithms.

Shib Sankar Bhowmick1, Debotosh Bhattacharjee2, Luis Rato3

  • 1Department of Electronics and Communication Engineering, Heritage Institute of Technology, Kolkata, 700107, India. shibsankar.bhowmick@heritageit.edu.

Genes & Genomics
|December 12, 2018
PubMed
Summary
This summary is machine-generated.

This study identifies robust gene biomarker signatures for common cancers using RNA-sequencing data and optimization algorithms. These biomarkers show high accuracy in distinguishing tumor from healthy samples, aiding in cancer diagnosis.

Keywords:
BiomarkerMachine learning toolsMessenger RNAOptimization algorithmPathway analysis

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Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Identifying differentially expressed genes is crucial for understanding biological conditions.
  • RNA-sequencing (RNA-seq) technology enables simultaneous measurement of transcript abundance for thousands of genes.

Purpose of the Study:

  • To identify cancer-specific biomarker signatures using next-generation sequencing (NGS) data for common cancer types.
  • To compare optimization algorithms for selecting gene sets that maximize classification accuracy between healthy and tumor samples.

Main Methods:

  • Utilized NGS data to identify differentially expressed genes using DESeq2.
  • Employed optimization algorithms including Artificial Bee Colony (ABC), Ant Colony Optimization, Differential Evolution, and Particle Swarm Optimization.
  • Classified samples using a support vector machine (SVM) model.

Main Results:

  • Achieved high classification accuracy for cancer-specific validation.
  • The ABC algorithm yielded the highest accuracy (99.10%) for Brain lower grade glioma.
  • Validation was supported by statistical tests and gene ontology/KEGG pathway enrichment analyses.

Conclusions:

  • Identified robust gene sets as potential biomarker signatures for various cancers.
  • These biomarkers may assist in the accurate identification of tumors of unknown origin.