title: PhenoNet: identification of key networks associated with disease phenotype.
abstract: BACKGROUND
  At the core of transcriptome analyses of cancer is a challenge to detect molecular differences affiliated with disease phenotypes. This approach has led to remarkable progress in identifying molecular signatures and in stratifying patients into clinical groups. Yet, despite this progress, many of the identified signatures are not robust enough to be clinically used and not consistent enough to provide a follow-up on molecular mechanisms.
  
  
  RESULTS
  To address these issues, we introduce PhenoNet, a novel algorithm for the identification of pathways and networks associated with different phenotypes. PhenoNet uses two types of input data: gene expression data (RMA, RPKM, FPKM, etc.) and phenotypic information, and integrates these data with curated pathways and protein-protein interaction information. Comprehensive iterations across all possible pathways and subnetworks result in the identification of key pathways or subnetworks that distinguish between the two phenotypes.
  
  
  METHODS
  Matlab code is available upon request.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.
authors.forename: Rotem
authors.initials: R
authors.lastname: Ben-Hamo
authors.affiliation: The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.
authors.forename: Moriah
authors.initials: M
authors.lastname: Gidoni
authors.affiliation: The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.
authors.forename: Sol
authors.initials: S
authors.lastname: Efroni
mesh_terms: D000465:Algorithms; D005260:Female; D015870:Gene Expression; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism*; D010641:Phenotype; D025941:Protein Interaction Mapping; D064726:Triple Negative Breast Neoplasms / Q000235:genetics / Q000378:metabolism