title: A global pathway crosstalk network.
abstract: BACKGROUND
  Given the complex nature of biological systems, pathways often need to function in a coordinated fashion in order to produce appropriate physiological responses to both internal and external stimuli. Therefore, understanding the interaction and crosstalk between pathways is important for understanding the function of both cells and more complex systems.
  
  
  RESULTS
  We have developed a computational approach to detect crosstalk among pathways based on protein interactions between the pathway components. We built a global mammalian pathway crosstalk network that includes 580 pathways (covering 4753 genes) with 1815 edges between pathways. This crosstalk network follows a power-law distribution: P(k) approximately k(-)(gamma), gamma = 1.45, where P(k) is the number of pathways with k neighbors, thus pathway interactions may exhibit the same scale-free phenomenon that has been documented for protein interaction networks. We further used this network to understand colorectal cancer progression to metastasis based on transcriptomic data.
  
  
  BACKGROUND
  yong.2.li@gsk.com
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Computational Biology, GlaxoSmithKline R&D, 709 Swedeland Road, UMW2230, King of Prussia, PA 19406, USA. yong.2.li@gsk.com
authors.forename: Yong
authors.initials: Y
authors.lastname: Li
authors.forename: Pankaj
authors.initials: P
authors.lastname: Agarwal
authors.forename: Dilip
authors.initials: D
authors.lastname: Rajagopalan
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008954:Models, Biological; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D020543:Proteome