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Conference Papers Year : 2021

Learning Boolean controls in regulated metabolic networks: a case-study

Abstract

Many techniques have been developed to infer Boolean regulations from a prior knowledge network and experimental data. Existing methods are able to reverse-engineer Boolean regulations for transcriptional and signaling networks, but they fail to infer regulations that control metabolic networks. This paper provides a formalisation of the inference of regulations for metabolic networks as a satisfiability problem with two levels of quantifiers, and introduces a method based on Answer Set Programming to solve this problem on a small-scale example.
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Dates and versions

hal-03207589 , version 1 (25-04-2021)
hal-03207589 , version 2 (06-05-2021)
hal-03207589 , version 3 (02-09-2021)

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Cite

Kerian Thuillier, Caroline Baroukh, Alexander Bockmayr, Ludovic Cottret, Loïc Paulevé, et al.. Learning Boolean controls in regulated metabolic networks: a case-study. CMSB 2021 - 19th International Conference on Computational Methods in Systems Biology, Sep 2021, Bordeaux, France. pp.159-180, ⟨10.1007/978-3-030-85633-5_10⟩. ⟨hal-03207589v3⟩
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