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Modelling Inhibition in Metabolic Pathways Through Abduction and Induction

  • Alireza Tamaddoni-Nezhad
  • Antonis Kakas
  • Stephen Muggleton
  • Florencio Pazos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3194)

Abstract

In this paper, we study how a logical form of scientific modelling that integrates together abduction and induction can be used to understand the functional class of unknown enzymes or inhibitors. We show how we can model, within Abductive Logic Programming (ALP), inhibition in metabolic pathways and use abduction to generate facts about inhibition of enzymes by a particular toxin (e.g. Hydrazine) given the underlying metabolic pathway and observations about the concentration of metabolites. These ground facts, together with biochemical background information, can then be generalised by ILP to generate rules about the inhibition by Hydrazine thus enriching further our model. In particular, using Progol 5.0 where the processes of abduction and inductive generalization are integrated enables us to learn such general rules. Experimental results on modelling in this way the effect of Hydrazine in a real metabolic pathway are presented.

Keywords

Nuclear Magnetic Resonance Metabolic Network Flux Balance Analysis Nuclear Magnetic Resonance Data Inductive Logic Programming 
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-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Alireza Tamaddoni-Nezhad
    • 1
  • Antonis Kakas
    • 2
  • Stephen Muggleton
    • 1
  • Florencio Pazos
    • 3
  1. 1.Department of ComputingImperial College LondonLondonUK
  2. 2.Dept. of Computer ScienceUniversity of Cyprus 
  3. 3.Dept. of Biological SciencesImperial College London 

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