Network biomarkers reveal dysfunctional gene regulations during disease progression

Abstract

Extensive studies have been conducted on gene biomarkers by exploring the increasingly accumulated gene expression and sequence data generated from high-throughput technology. Here, we briefly report on the state-of-the-art research and application of biomarkers from single genes (i.e. gene biomarkers) to gene sets (i.e. group or set biomarkers), gene networks (i.e. network biomarkers) and dynamical gene networks (i.e. dynamical network biomarkers). In particular, differential and dynamical network biomarkers are used as representative examples to demonstrate their effectiveness in both detecting early signals for complex diseases and revealing essential mechanisms on disease initiation and progression at a network level. Here, we briefly report on the state-of-the-art research and application of biomarkers from single genes to gene sets, gene networks and dynamical gene networks, which explore the increasingly-accumulated gene expression and sequence data. Differential network biomarkers and dynamical network biomarkers are used as representative examples to demonstrate their effectiveness on detecting early signals for complex diseases and revealing essential pathogen mechanisms. © 2013 FEBS.