• differential expression network;
  • disease diagnosis;
  • disease prognosis;
  • disease progression;
  • dynamical network biomarkers;
  • gene regulation;
  • module biomarkers;
  • network biomarkers;
  • progressive module network model;
  • systems biology

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.