50 Shades of Rule Composition

From Chemical Reactions to Higher Levels of Abstraction
  • Jakob Lykke Andersen
  • Christoph Flamm
  • Daniel Merkle
  • Peter F. Stadler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8738)


Graph rewriting has been applied quite successfully to model chemical and biological systems at different levels of abstraction. A particularly powerful feature of rule-based models that are rigorously grounded in category theory, is, that they admit a well-defined notion of rule composition, hence, provide their users with an intrinsic mechanism for compressing trajectories and coarse grained representations of dynamical aspects. The same formal framework, however, also allows the detailed analysis of transitions in which the final and initial states are known, but the detailed stepwise mechanism remains hidden. To demonstrate the general principle we consider here how rule composition is used to determine accurate atom maps for complex enzyme reactions. This problem not only exemplifies the paradigm but is also of considerable practical importance for many down-stream analyses of metabolic networks and it is a necessary prerequisite for predicting atom traces for the analysis of isotope labelling experiments.


Transformation Rule Rule Composition Identity Rule Common Subgraph Context Graph 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Jakob Lykke Andersen
    • 1
  • Christoph Flamm
    • 2
  • Daniel Merkle
    • 1
  • Peter F. Stadler
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
  1. 1.Department of Mathematics and Computer ScienceUniversity of Southern DenmarkDenmark
  2. 2.Institute for Theoretical ChemistryUniversity of ViennaAustria
  3. 3.Department of Computer Science, and Interdisciplinary Center for BioinformaticsBioinformatics GroupLeipzigGermany
  4. 4.Max Planck Institute for Mathematics in the SciencesLeipzigGermany
  5. 5.Fraunhofer Institute for Cell Therapy and ImmunologyLeipzigGermany
  6. 6.Center for Non-coding RNA in Technology and HealthUniversity of CopenhagenDenmark
  7. 7.Santa Fe InstituteUSA

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