title: Identifying disease genes and module biomarkers by differential interactions.
abstract: OBJECTIVE
  A complex disease is generally caused by the mutation of multiple genes or by the dysfunction of multiple biological processes. Systematic identification of causal disease genes and module biomarkers can provide insights into the mechanisms underlying complex diseases, and help develop efficient therapies or effective drugs.
  
  
  METHODS
  In this paper, we present a novel approach to predict disease genes and identify dysfunctional networks or modules, based on the analysis of differential interactions between disease and control samples, in contrast to the analysis of differential gene or protein expressions widely adopted in existing methods.
  
  
  CONCLUSIONS
  As an example, we applied our method to the study of three-stage microarray data for gastric cancer. We identified network modules or module biomarkers that include a set of genes related to gastric cancer, implying the predictive power of our method. The results on holdout validation data sets show that our identified module can serve as an effective module biomarker for accurately detecting or diagnosing gastric cancer, thereby validating the efficiency of our method.
  
  
  CONCLUSIONS
  We proposed a new approach to detect module biomarkers for diseases, and the results on gastric cancer demonstrated that the differential interactions are useful to detect dysfunctional modules in the molecular interaction network, which in turn can be used as robust module biomarkers.
authors.affiliation: Institute of Systems Biology, Shanghai University, Shanghai, China.
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Liu
authors.forename: Zhi-Ping
authors.initials: ZP
authors.lastname: Liu
authors.forename: Xing-Ming
authors.initials: XM
authors.lastname: Zhao
authors.forename: Luonan
authors.initials: L
authors.lastname: Chen
mesh_terms: D015415:Biomarkers / Q000032:analysis; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks; D005819:Genetic Markers; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D060066:Protein Interaction Maps / Q000235:genetics; D013274:Stomach Neoplasms / Q000235:genetics*
chemical_list: D015415:Biomarkers; D005819:Genetic Markers