title: A method for developing regulatory gene set networks to characterize complex biological systems.
abstract: BACKGROUND
  Traditional approaches to studying molecular networks are based on linking genes or proteins. Higher-level networks linking gene sets or pathways have been proposed recently. Several types of gene set networks have been used to study complex molecular networks such as co-membership gene set networks (M-GSNs) and co-enrichment gene set networks (E-GSNs). Gene set networks are useful for studying biological mechanism of diseases and drug perturbations.
  
  
  RESULTS
  In this study, we proposed a new approach for constructing directed, regulatory gene set networks (R-GSNs) to reveal novel relationships among gene sets or pathways. We collected several gene set collections and high-quality gene regulation data in order to construct R-GSNs in a comparative study with co-membership gene set networks (M-GSNs). We described a method for constructing both global and disease-specific R-GSNs and determining their significance. To demonstrate the potential applications to disease biology studies, we constructed and analysed an R-GSN specifically built for Alzheimer's disease.
  
  
  CONCLUSIONS
  R-GSNs can provide new biological insights complementary to those derived at the protein regulatory network level or M-GSNs. When integrated properly to functional genomics data, R-GSNs can help enable future research on systems biology and translational bioinformatics.
authors.forename: Chayaporn
authors.initials: C
authors.lastname: Suphavilai
authors.forename: Liugen
authors.initials: L
authors.lastname: Zhu
authors.forename: Jake Y
authors.initials: JY
authors.lastname: Chen
mesh_terms: D000544:Alzheimer Disease / Q000235:genetics; D030541:Databases, Genetic; D053263:Gene Regulatory Networks; D006801:Humans; D049490:Systems Biology / Q000379:methods*