Computing Difference Abstractions of Linear ...
Document type :
Article dans une revue scientifique: Article original
Title :
Computing Difference Abstractions of Linear Equation Systems
Author(s) :
Allart, Emilie [Auteur]
BioComputing
Niehren, Joachim [Auteur]
BioComputing
Linking Dynamic Data [LINKS]
Versari, Cristian [Auteur]
BioComputing
BioComputing
Niehren, Joachim [Auteur]

BioComputing
Linking Dynamic Data [LINKS]
Versari, Cristian [Auteur]

BioComputing
Journal title :
Theoretical Computer Science
Publisher :
Elsevier
Publication date :
2021
ISSN :
0304-3975
English keyword(s) :
boolean abstraction
metabolic networks
synthetic biology
systems biology
reaction networks
gene knockout prediction
first-order definitions
constraint programming
abstract interpretation
metabolic networks
synthetic biology
systems biology
reaction networks
gene knockout prediction
first-order definitions
constraint programming
abstract interpretation
HAL domain(s) :
Informatique [cs]/Bio-informatique [q-bio.QM]
Informatique [cs]/Calcul formel [cs.SC]
Mathématiques [math]/Logique [math.LO]
Informatique [cs]/Calcul formel [cs.SC]
Mathématiques [math]/Logique [math.LO]
English abstract : [en]
Abstract interpretation was proposed for predicting changes of reaction networks with partial kinetic information in systems biology. This requires to compute the set of difference abstractions of a system of linear equations ...
Show more >Abstract interpretation was proposed for predicting changes of reaction networks with partial kinetic information in systems biology. This requires to compute the set of difference abstractions of a system of linear equations under nonlinear constraints. We present the first practical algorithm that can compute the difference abstractions of linear equation systems exactly. We also present a new heuristics based on minimal support consequences for overapproximating the set of difference abstractions. Our algorithms rely on elementary modes, first-order definitions, and finite domain constraint programming. We implemented our algorithms and applied them to change prediction in systems biology. It turns out experimentally that the new heuristics is often exact in practice, while outperforming the exact algorithm.Show less >
Show more >Abstract interpretation was proposed for predicting changes of reaction networks with partial kinetic information in systems biology. This requires to compute the set of difference abstractions of a system of linear equations under nonlinear constraints. We present the first practical algorithm that can compute the difference abstractions of linear equation systems exactly. We also present a new heuristics based on minimal support consequences for overapproximating the set of difference abstractions. Our algorithms rely on elementary modes, first-order definitions, and finite domain constraint programming. We implemented our algorithms and applied them to change prediction in systems biology. It turns out experimentally that the new heuristics is often exact in practice, while outperforming the exact algorithm.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Comment :
This is an extension of a previous publication, see hal-02302463v1.
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