PanARGMiner (Pan-Genomic Antimicrobial Resistance Gene Miner): An advanced feature selection framework for extracting key resistance genes from pan-genomic datasets.

ABSTRACT: Identifying antimicrobial resistance (AMR)-related biomarkers from large-scale genomic datasets is often akin to finding a needle in a haystack. With pan-genomic data containing more than 100,000 gene sequences, isolating features that truly drive resistance remains a major challenge in computational biology. Here we present PanARGMiner, a machine learning-based feature selection framework designed to robustly extract highly relevant and informative biomarkers from high-dimensional biological data. PanARGMiner uses an ensemble-based feature selection strategy to select highly informative and compact feature subsets. It then utilizes repeated iterations to ensure the stability and reliability of the proposed framework, enabling PanARGMiner to generate significantly reduced features with com

SUBMITTER: Chen YC 

PROVIDER: S-EPMC12699266 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature