title: Finding disease specific alterations in the co-expression of genes.
abstract: BACKGROUND
  Standard analysis routines for microarray data aim at differentially expressed genes. In this paper, we address the complementary problem of detecting sets of differentially co-expressed genes in two phenotypically distinct sets of expression profiles.
  
  
  RESULTS
  We introduce a score for differential co-expression and suggest a computationally efficient algorithm for finding high scoring sets of genes. The use of our novel method is demonstrated in the context of simulations and on real expression data from a clinical study.
authors.affiliation: Max Planck Institute for Molecular Genetics, Berlin, Germany. dennis.kostka@molgen.mpg.de
authors.forename: Dennis
authors.initials: D
authors.lastname: Kostka
authors.forename: Rainer
authors.initials: R
authors.lastname: Spang
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D007938:Leukemia / Q000175:diagnosis* / Q000378:metabolism*; D005810:Multigene Family; D009363:Neoplasm Proteins / Q000032:analysis*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins