title: Modeling mechanistic biological networks: an advanced Boolean approach.
abstract: BACKGROUND
  The understanding of the molecular sources for diseases like cancer can be significantly improved by computational models. Recently, Boolean networks have become very popular for modeling signaling and regulatory networks. However, such models rely on a set of Boolean functions that are in general not known. Unfortunately, while detailed information on the molecular interactions becomes available in large scale through electronic databases, the information on the Boolean functions does not become available simultaneously and has to be included manually into the models, if at all known.
  
  
  RESULTS
  We propose a new Boolean approach which can directly utilize the mechanistic network information available through modern databases. The Boolean function is implicitly defined by the reaction mechanisms. Special care has been taken for the treatment of kinetic features like inhibition. The method has been applied to a signaling model combining the Wnt and MAPK pathway.
  
  
  BACKGROUND
  A sample C++ implementation of the proposed method is available for Linux and compatible systems through http://code.google.com/p/libscopes/wiki/Paper2011.
authors.affiliation: Department of Theoretical Biophysics, Humboldt-Universität zu Berlin, Invalidenstr. 42, 10115 Berlin, Germany. handorf@physik.hu-berlin.de
authors.forename: T
authors.initials: T
authors.lastname: Handorf
authors.forename: E
authors.initials: E
authors.lastname: Klipp
mesh_terms: D003198:Computer Simulation; D016208:Databases, Factual; D053263:Gene Regulatory Networks; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D015398:Signal Transduction