Graph-Based Decomposition of Biochemical Reaction Networks into Monotone Subsystems

  • Hans-Michael Kaltenbach
  • Simona Constantinescu
  • Justin Feigelman
  • Jörg Stelling
Conference paper

DOI: 10.1007/978-3-642-23038-7_13

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6833)
Cite this paper as:
Kaltenbach HM., Constantinescu S., Feigelman J., Stelling J. (2011) Graph-Based Decomposition of Biochemical Reaction Networks into Monotone Subsystems. In: Przytycka T.M., Sagot MF. (eds) Algorithms in Bioinformatics. WABI 2011. Lecture Notes in Computer Science, vol 6833. Springer, Berlin, Heidelberg

Abstract

Large-scale model development for biochemical reaction networks of living cells is currently possible through qualitative model classes such as graphs, Boolean logic, or Petri nets. However, when it is important to understand quantitative dynamic features of a system, uncertainty about the networks often limits large-scale model development. Recent results, especially from monotone systems theory, suggest that structural network constraints can allow consistent system decompositions, and thus modular solutions to the scaling problem. Here, we propose an algorithm for the decomposition of large networks into monotone subsystems, which is a computationally hard problem. In contrast to prior methods, it employs graph mapping and iterative, randomized refinement of modules to approximate a globally optimal decomposition with homogeneous modules and minimal interfaces between them. Application to a medium-scale model for signaling pathways in yeast demonstrates that our algorithm yields efficient and biologically interpretable modularizations; both aspects are critical for extending the scope of (quantitative) cellular network analysis.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Hans-Michael Kaltenbach
    • 1
  • Simona Constantinescu
    • 2
  • Justin Feigelman
    • 2
  • Jörg Stelling
    • 1
    • 2
  1. 1.Dep. Biosystems Science and EngineeringETH ZurichBaselSwitzerland
  2. 2.Dep. Computer ScienceETH ZurichZurichSwitzerland

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