title: Network and matrix analysis of the respiratory disease interactome.
abstract: BACKGROUND
  Although respiratory diseases exhibit in a wide array of clinical manifestations, certain respiratory diseases may share related genetic mechanisms or may be influenced by similar chemical stimuli. Here we explore and infer relationships among genes, diseases, and chemicals using network and matrix based clustering methods.
  
  
  RESULTS
  In order to better understand and elucidate these shared genetic mechanisms and chemical relationships we analyzed a comprehensive collection of gene, disease, and chemical relationships pertinent to respiratory disease, using network and matrix based analysis approaches. Our methods enabled us to analyze relationships and make biological inferences among over 200 different respiratory and related diseases, involving thousands of gene-chemical-disease relationships.
  
  
  CONCLUSIONS
  The resulting networks provided insight into shared mechanisms of respiratory disease and in some cases suggest novel targets or repurposed drug strategies.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Garcia
authors.forename: Gargi
authors.initials: G
authors.lastname: Datta
authors.forename: Gregory P
authors.initials: GP
authors.lastname: Cosgrove
authors.affiliation: Integrated Center for Genes, Environment, and Health, National Jewish Health, Denver, CO 80206, USA. StrongM@NJHealth.org.
authors.forename: Michael
authors.initials: M
authors.lastname: Strong
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology; D012140:Respiratory Tract Diseases / Q000235:genetics* / Q000378:metabolism*; D049490:Systems Biology / Q000379:methods*