title: FogLight: an efficient matrix-based approach to construct metabolic pathways by search space reduction.
abstract: BACKGROUND
  A fundamental computational problem in the area of metabolic engineering is finding metabolic pathways between a pair of source and target metabolites efficiently. We present an approach, namely FogLight, for searching metabolic networks utilizing Boolean (AND-OR) operations represented in matrix notation to efficiently reduce the search space. This enables the enumeration of all pathways between metabolites that are too distant for the application of brute-force methods.
  
  
  RESULTS
  Benchmarking tests run with FogLight show that it can reduce the search space by up to 98%, after which the accelerated search for high accurate results is guaranteed. Using FogLight, several pathways between eight given pairs of metabolites are found of which the pathways from CO2 to ethanol are specifically discussed. Additionally, in comparison with three path-finding tools, namely PHT, FMM and RouteSearch, FogLight can find shorter and more pathways for attempted source-target metabolite pairs.
  
  
  BACKGROUND
  szamani@aut.ac.ir, gholamreza.bidkhori@vtt.fi
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Computer Engineering & IT, Amirkabir University of Technology, Tehran, Iran and.
authors.forename: Mehrshad
authors.initials: M
authors.lastname: Khosraviani
authors.affiliation: Department of Computer Engineering & IT, Amirkabir University of Technology, Tehran, Iran and.
authors.forename: Morteza
authors.initials: M
authors.lastname: Saheb Zamani
authors.affiliation: Department of Computer Engineering & IT, Amirkabir University of Technology, Tehran, Iran and.
authors.forename: Gholamreza
authors.initials: G
authors.lastname: Bidkhori
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D060847:Metabolic Engineering / Q000379:methods*; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological; D012984:Software