Record number :
497875
Title of article :
Algorithmic and complexity results for decompositions of biological networks into monotone subsystems
Author/Authors :
Bhaskar DasGupta، نويسنده , , German Andres Enciso، نويسنده , , Eduardo Sontag، نويسنده , , Yi Zhang، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
Pages :
18
From page :
161
To page :
178
Abstract :
A useful approach to the mathematical analysis of large-scale biological networks is based upon their decompositions into monotone dynamical systems. This paper deals with two computational problems associated to finding decompositions which are optimal in an appropriate sense. In graph-theoretic language, the problems can be recast in terms of maximal sign-consistent subgraphs. The theoretical results include polynomial-time approximation algorithms as well as constant-ratio inapproximability results. One of the algorithms, which has a worst-case guarantee of 87.9% from optimality, is based on the semidefinite programming relaxation approach of Goemans–Williamson [Goemans, M., Williamson, D., 1995. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. J. ACM 42 (6), 1115–1145]. The algorithm was implemented and tested on a Drosophila segmentation network and an Epidermal Growth Factor Receptor pathway model, and it was found to perform close to optimally.
Keywords :
approximation algorithms , Biological networks , Sign-consistent subgraphs , semidefinite programming , Monotone dynamical systems
Journal title :
BioSystems
Serial Year :
2007
Link To Document :
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