GeneCompete: an integrative tool of a novel union algorithm with various ranking techniques for multiple gene expression data.

ABSTRACT:

Background

Identifying the genes responsible for diseases requires precise prioritization of significant genes. Gene expression analysis enables differentiation between gene expressions in disease and normal samples. Increasing the number of high-quality samples enhances the strength of evidence regarding gene involvement in diseases. This process has led to the discovery of disease biomarkers through the collection of diverse gene expression data.

Methods

This study presents GeneCompete, a web-based tool that integrates gene expression data from multiple platforms and experiments to identify the most promising biomarkers. GeneCompete incorporates a novel union strategy and eight well-established ranking methods, including Win-Loss, Massey, Colley, Keener, Elo, Markov, PageR

SUBMITTER: Janyasupab P 

PROVIDER: S-EPMC10703088 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature