Title :

Knockout Prediction for Reaction Networks with Partial Kinetic Information

Author(s) :

John, Mathias [Auteur correspondant]
Programming Languages for Biological Modeling and Simulation [BioComputing]
Nebut, Mirabelle [Auteur]
Programming Languages for Biological Modeling and Simulation [BioComputing]
Niehren, Joachim [Auteur]
Programming Languages for Biological Modeling and Simulation [BioComputing]
Centre Inria de l'Université de Lille

Conference title :

14th International Conference on Verification, Model Checking, and Abstract Interpretation

City :

Rome

Country :

Italie

Start date of the conference :

2013-01-20

Journal title :

Lecture Notes in Computer Science

Publisher :

Springer

Publication date :

2013-01-20

English keyword(s) :

metabolic networks
Constraint programming
abstract interpretation
systems biology
genetic engineering
metabolic networks.

HAL domain(s) :

Informatique [cs]/Bio-informatique [q-bio.QM]
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
Informatique [cs]/Langage de programmation [cs.PL]
Informatique [cs]/Logique en informatique [cs.LO]

English abstract : [en]

In synthetic biology, a common application field for computational methods is the prediction of knockout strategies for reaction networks. Thereby, the major challenge is the lack of information on reaction kinetics. In ...
Show more >In synthetic biology, a common application field for computational methods is the prediction of knockout strategies for reaction networks. Thereby, the major challenge is the lack of information on reaction kinetics. In this paper, we propose an approach, based on abstract interpretation, to predict candidates for reaction knockouts, relying only on partial kinetic information. We consider the usual deterministic steady state semantics of reaction networks and a few general properties of reaction kinetics. We introduce a novel abstract domain over pairs of real domain values to compute the differences between steady states that are reached before and after applying some knockout. We show that this abstract domain allows us to predict correct knockout strategy candidates independent of any particular choice of reaction kinetics. Our predictions remain candidates, since our abstract interpretation over-approximates the solution space. We provide an operational semantics for our abstraction in terms of constraint satisfaction problems and illustrate our approach on a realistic network. An extended version of this paper with appendices containing detailed information on proofs and on the example model is provided at http://www.lifl.fr/BioComputing/extendedPapers/vmcai13.pdf. Keywords: Abstract interpretation, deterministic semantics, steady state, constraint satisfaction, synthetic biology.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL