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Application of abductive ILP to learning metabolic network inhibition from temporal data

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Tamaddoni-Nezhad, Alireza, Chaleil, Raphael, Kakas, Antonis, Muggleton, Stephen·2006·Machine Learning
DOI 10.1007/s10994-006-8988-x
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  • ILP has been applied to modelling inhibition in metabolic networks.

    “modelling inhibition in metabolic networks (Tamaddoni-Nezhad et al., 2006)”

    From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Tamaddoni-Nezhad et al., 2006

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Cited by

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Authors
Tamaddoni-Nezhad, A., Chaleil, R., Kakas, A., & Muggleton, S.
Affiliations
  • University of Cyprus (CY)
  • Imperial College London (GB)
ORCID
Venue
Machine Learning
Publisher
Springer Science and Business Media LLC
Published
2006-06-30
Volume
64
Issue
1-3
Pages
209-230
ISSN
  • 0885-6125 (ISSN-L)
  • 1573-0565
DOI
10.1007/s10994-006-8988-x
OpenAlex
W2135498576
Cited by
92
References
2
Citations by year
2024: 1 · 2023: 1 · 2022: 2 · 2021: 3 · 2020: 3 · 2019: 1 · 2018: 3 · 2017: 4 · 2016: 1 · 2015: 2 · 2014: 4 · 2013: 11 · 2012: 6
FWCI
4.63
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
Machine Learning (publishedVersion)
Funders
Imperial College London
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
Keywords
enzyme inhibition, metabolic networks, drug side effect prediction, NMR metabolomics, rat urine

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