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The NetGenerator Algorithm: Reconstruction of Gene Regulatory Networks

  • Susanne Toepfer
  • Reinhard Guthke
  • Dominik Driesch
  • Dirk Woetzel
  • Michael Pfaff
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4366)

Abstract

Mathematical models of gene regulatory networks aim to capture the causal regulatory relationships by fitting the network models to monitored time courses of gene expression levels. In this paper, the NetGenerator algorithm is presented that generates mathematical models in form of linear or nonlinear differential equation systems. The problem of finding the most likely interactions between genes is solved by a structure identification method. This can also be effectively supported by the incorporation of available expert knowledge. Using favorable parameter identification methods from a system identification point of view allows to fit accurate and sparsely connected models. By the inclusion of higher order submodels, the algorithm enables the identification of gene-gene interactions with significantly time delayed gene regulation.

Keywords

Gene Regulatory Network External Input Optimization Loop Interpretable Model Structure Primary Mouse Hepatocyte 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Susanne Toepfer
    • 1
  • Reinhard Guthke
    • 2
  • Dominik Driesch
    • 1
  • Dirk Woetzel
    • 1
  • Michael Pfaff
    • 1
  1. 1.BioControl Jena GmbH, Wildenbruchstr. 15, D-07745 JenaGermany
  2. 2.Leibniz Institute for Natural Product Research and Infection Biology - Hans Knoell Institute, Beutenbergstr. 11a, D-07745 JenaGermany

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