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Hybrid metabolic network completion

  • Metabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an answer set programming (ASP)-based approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system dingo for solving theMetabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an answer set programming (ASP)-based approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system dingo for solving the resulting logic program with linear constraints over reals. We empirically evaluate our approach by means of the metabolic network of Escherichia coli. Our analysis shows that our novel approach yields greatly superior results than obtainable from purely qualitative or quantitative approaches.show moreshow less

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Metadaten
Author details:Clémence FriouxORCiD, Torsten H. SchaubORCiDGND, Sebastian SchellhornORCiD, Anne SiegelORCiDGND, Philipp WankoORCiD
DOI:https://doi.org/10.1017/S1471068418000455
ISSN:1471-0684
ISSN:1475-3081
Title of parent work (English):Theory and practice of logic programming
Publisher:Cambridge University Press
Place of publishing:New York
Publication type:Article
Language:English
Date of first publication:2018/11/09
Publication year:2019
Release date:2021/05/28
Tag:answer set programming; bioinformatics; gap-filling; hybrid solving; linear programming; metabolic network
Volume:19
Issue:1
Number of pages:26
First page:83
Last Page:108
Funding institution:DFGGerman Research Foundation (DFG) [SCHA 550/9, 11]; French Government via the National Research Agency investment expenditure program IDEALG [ANR-10-BTBR-04]
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Informatik und Computational Science
DDC classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
Peer review:Referiert
Publishing method:Open Access / Green Open-Access
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