title: Differential network analysis for the identification of condition-specific pathway activity and regulation.
abstract: BACKGROUND
  Identification of differential expressed genes has led to countless new discoveries. However, differentially expressed genes are only a proxy for finding dysregulated pathways. The problem is to identify how the network of regulatory and physical interactions rewires in different conditions or in disease.
  
  
  RESULTS
  We developed a procedure named DINA (DIfferential Network Analysis), which is able to identify set of genes, whose co-regulation is condition-specific, starting from a collection of condition-specific gene expression profiles. DINA is also able to predict which transcription factors (TFs) may be responsible for the pathway condition-specific co-regulation. We derived 30 tissue-specific gene networks in human and identified several metabolic pathways as the most differentially regulated across the tissues. We correctly identified TFs such as Nuclear Receptors as their main regulators and demonstrated that a gene with unknown function (YEATS2) acts as a negative regulator of hepatocyte metabolism. Finally, we showed that DINA can be used to make hypotheses on dysregulated pathways during disease progression. By analyzing gene expression profiles across primary and transformed hepatocytes, DINA identified hepatocarcinoma-specific metabolic and transcriptional pathway dysregulation.
  
  
  BACKGROUND
  We implemented an on-line web-tool http://dina.tigem.it enabling the user to apply DINA to identify tissue-specific pathways or gene signatures.
  
  
  BACKGROUND
  dibernardo@tigem.it
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: The Telethon Institute of Genetics and Medicine TIGEM.
authors.forename: Gennaro
authors.initials: G
authors.lastname: Gambardella
authors.forename: Maria Nicoletta
authors.initials: MN
authors.lastname: Moretti
authors.forename: Rossella
authors.initials: R
authors.lastname: de Cegli
authors.forename: Luca
authors.initials: L
authors.lastname: Cardone
authors.forename: Adriano
authors.initials: A
authors.lastname: Peron
authors.forename: Diego
authors.initials: D
authors.lastname: di Bernardo
mesh_terms: D000818:Animals; D006528:Carcinoma, Hepatocellular / Q000235:genetics / Q000378:metabolism; D045744:Cell Line, Tumor; D002478:Cells, Cultured; D019295:Computational Biology / Q000379:methods; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D022781:Hepatocytes / Q000378:metabolism; D006801:Humans; D008113:Liver Neoplasms / Q000235:genetics / Q000378:metabolism; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D051379:Mice; D009928:Organ Specificity; D014157:Transcription Factors / Q000378:metabolism; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism
chemical_list: D014157:Transcription Factors; D016159:Tumor Suppressor Protein p53