title: graphite - a Bioconductor package to convert pathway topology to gene network.
abstract: BACKGROUND
  Gene set analysis is moving towards considering pathway topology as a crucial feature. Pathway elements are complex entities such as protein complexes, gene family members and chemical compounds. The conversion of pathway topology to a gene/protein networks (where nodes are a simple element like a gene/protein) is a critical and challenging task that enables topology-based gene set analyses.Unfortunately, currently available R/Bioconductor packages provide pathway networks only from single databases. They do not propagate signals through chemical compounds and do not differentiate between complexes and gene families.
  
  
  RESULTS
  Here we present graphite, a Bioconductor package addressing these issues. Pathway information from four different databases is interpreted following specific biologically-driven rules that allow the reconstruction of gene-gene networks taking into account protein complexes, gene families and sensibly removing chemical compounds from the final graphs. The resulting networks represent a uniform resource for pathway analyses. Indeed, graphite provides easy access to three recently proposed topological methods. The graphite package is available as part of the Bioconductor software suite.
  
  
  CONCLUSIONS
  graphite is an innovative package able to gather and make easily available the contents of the four major pathway databases. In the field of topological analysis graphite acts as a provider of biological information by reducing the pathway complexity considering the biological meaning of the pathway elements.
authors.affiliation: Department of Biology, University of Padova, via U, Bassi 58/B, Padova, Italy.
authors.forename: Gabriele
authors.initials: G
authors.lastname: Sales
authors.forename: Enrica
authors.initials: E
authors.lastname: Calura
authors.forename: Duccio
authors.initials: D
authors.lastname: Cavalieri
authors.forename: Chiara
authors.initials: C
authors.lastname: Romualdi
mesh_terms: D053263:Gene Regulatory Networks; D006801:Humans; D007328:Insulin / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D051881:Receptor, Notch1 / Q000378:metabolism; D015398:Signal Transduction; D012984:Software
chemical_list: D007328:Insulin; C497761:NOTCH1 protein, human; D051881:Receptor, Notch1