title: A fast and efficient gene-network reconstruction method from multiple over-expression experiments.
abstract: BACKGROUND
  Reverse engineering of gene regulatory networks presents one of the big challenges in systems biology. Gene regulatory networks are usually inferred from a set of single-gene over-expressions and/or knockout experiments. Functional relationships between genes are retrieved either from the steady state gene expressions or from respective time series.
  
  
  RESULTS
  We present a novel algorithm for gene network reconstruction on the basis of steady-state gene-chip data from over-expression experiments. The algorithm is based on a straight forward solution of a linear gene-dynamics equation, where experimental data is fed in as a first predictor for the solution. We compare the algorithm's performance with the NIR algorithm, both on the well known E. coli experimental data and on in-silico experiments.
  
  
  CONCLUSIONS
  We show superiority of the proposed algorithm in the number of correctly reconstructed links and discuss computational time and robustness. The proposed algorithm is not limited by combinatorial explosion problems and can be used in principle for large networks.
authors.affiliation: Complex Systems Research Group, Medical University of Vienna, A-1090, Austria. stokic@swissquant.ch
authors.forename: Dejan
authors.initials: D
authors.lastname: Stokić
authors.forename: Rudolf
authors.initials: R
authors.lastname: Hanel
authors.forename: Stefan
authors.initials: S
authors.lastname: Thurner
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D053263:Gene Regulatory Networks; D049490:Systems Biology
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