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Detecting inconsistencies in large biological networks with answer set programming

  • We introduce an approach to detecting inconsistencies in large biological networks by using answer set programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach based on answer set programming to check the consistency of large-scale data sets. Moreover, we extend this methodology to provide explanations for inconsistencies by determining minimal representations of conflicts. In practice, this can be used to identify unreliable data or to indicate missing reactions.

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Metadaten
Author:Martin GebserORCiD, Torsten SchaubORCiDGND, Sven ThieleORCiDGND, Philippe Veber
URN:urn:nbn:de:kobv:517-opus4-412467
DOI:https://doi.org/10.25932/publishup-41246
ISSN:1866-8372
Parent Title (English):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
Series (Serial Number):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (561)
Document Type:Postprint
Language:English
Date of first Publication:2019/01/30
Year of Completion:2011
Publishing Institution:Universität Potsdam
Release Date:2019/01/30
Tag:answer set programming; bioinformatics; consistency; diagnosis
Issue:561
Pagenumber:38
Source:Theory and Practice of Logic Programming 11 (2011) 2–3, pp. 323–360 DOI 10.1017/S1471068410000554
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Peer Review:Referiert
Publication Way:Open Access
Grantor:Cambridge University Press (CUP)
Licence (German):License LogoKeine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht
Notes extern:Bibliographieeintrag der Originalveröffentlichung/Quelle