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

You might also read

Related Articles

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

Sort by

Same author

First-Line Enfortumab Vedotin Plus Pembrolizumab vs Gemcitabine Plus Cisplatin for Metastatic Urothelial Carcinoma.

JAMA network open·2026

Same author

Comparative analysis of genitourinary toxicity following bladder outlet obstruction procedures in patients before versus after radiotherapy for localized prostate cancer: a retrospective cohort study using the TriNetX database.

Prostate cancer and prostatic diseases·2026

Same author

Associations between erectile dysfunction, low testosterone, and cardiometabolic risk: an age stratified, propensity-matched cohort study.

International journal of impotence research·2026

Same author

Addition of immune checkpoint inhibitors to intravesical BCG for high-risk BCG-naïve non-muscle invasive bladder cancer: Systematic review and meta-analysis.

BJUI compass·2026

Same author

Coverage, Traits, and Geographic Distribution of Online Surgeon Reviews: Large-Scale Cross-Sectional Analysis.

JMIR formative research·2026

Same author

Real-world functional and oncologic outcomes of prostate gland ablation vs. standard of care therapies for localized prostate: A retrospective cohort study using the TriNetX database.

Urologic oncology·2026

Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026

Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026

Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026

Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026

Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026

Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 8, 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

A New Combinatorial Optimization Approach for Integrated Feature Selection Using Different Datasets: A Prostate

Nisha Puthiyedth¹, Carlos Riveros¹, Regina Berretta¹

¹Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia; School of Electrical Engineering and Computer Science, The University of Newcastle, Callaghan NSW, Australia.

|June 25, 2015

Summary

This summary is machine-generated.

Integrating multiple transcriptomic datasets using a novel combinatorial optimization model enhances biomarker discovery for prostate cancer. This approach identifies more informative gene signatures than traditional methods, improving statistical power and disease subgroup marker detection.

More Related Videos

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

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

Related Experiment Videos

Last Updated: Apr 8, 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: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

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

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Joint analysis of multiple datasets increases statistical power for biomarker detection, especially in smaller studies.
This meta-analysis approach is common in transcriptomic and genome-wide association studies.
Existing methods lack advanced combinatorial optimization for dataset integration.

Purpose of the Study:

Introduce a new combinatorial optimization model for integrating multiple datasets.
Apply the model to transcriptomic data for enhanced biomarker discovery.
Address limitations in current meta-analysis techniques.

Main Methods:

Developed a generalized combinatorial optimization problem based on the (α,β)-k-Feature Set problem.
Applied the model to a meta-analysis of six prostate cancer microarray datasets.
Compared results against RankProd and individual dataset analyses.

Main Results:

The integrated method yielded a more informative gene signature compared to RankProd and individual analyses.
Identified a highly significant set of genes relevant to prostate cancer.
The method effectively captures markers for disease subgroups without data homogenization.

Conclusions:

The proposed combinatorial optimization model offers a powerful approach for multi-dataset integration in transcriptomics.
This method improves biomarker discovery and overcomes challenges with real-world heterogeneous datasets.
The findings highlight the potential for advanced computational models in precision oncology.