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A Graph Theoretical Approach for Testing Binomiality of Reversible Chemical Reaction Networks
- Source :
- 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing-SYNASC 2020, 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing-SYNASC 2020, Sep 2020, Timisoara/Virtual, Romania, SYNASC
- Publication Year :
- 2020
- Publisher :
- arXiv, 2020.
-
Abstract
- International audience; We study binomiality of the steady state ideals of chemical reaction networks. Considering rate constants as indeterminates, the concept of unconditional binomiality has been introduced and an algorithm based on linear algebra has been proposed in a recent work for reversible chemical reaction networks, which has a polynomial time complexity upper bound on the number of species and reactions. In this article, using a modified version of species--reaction graphs, we present an algorithm based on graph theory which performs by adding and deleting edges and changing the labels of the edges in order to test unconditional binomiality. We have implemented our graph theoretical algorithm as well as the linear algebra one in Maple and made experiments on biochemical models. Our experiments show that the performance of the graph theoretical approach is similar to or better than the linear algebra approach, while it is drastically faster than Groebner basis and quantifier elimination methods.
- Subjects :
- 0301 basic medicine
Computer Science - Symbolic Computation
FOS: Computer and information sciences
Binomial Ideals
[MATH.MATH-AC]Mathematics [math]/Commutative Algebra [math.AC]
Symbolic Computation (cs.SC)
Commutative Algebra (math.AC)
01 natural sciences
Upper and lower bounds
010305 fluids & plasmas
[MATH.MATH-AC] Mathematics [math]/Commutative Algebra [math.AC]
03 medical and health sciences
Gröbner basis
0103 physical sciences
Quantifier elimination
ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION
[SDV.BBM] Life Sciences [q-bio]/Biochemistry, Molecular Biology
FOS: Mathematics
[SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology
Commutative algebra
Time complexity
Reversible Chemical Reaction Networks
Mathematics
Discrete mathematics
[INFO.INFO-SC]Computer Science [cs]/Symbolic Computation [cs.SC]
[INFO.INFO-SC] Computer Science [cs]/Symbolic Computation [cs.SC]
Graph theory
[SDV.BBM.MN]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular Networks [q-bio.MN]
Symbolic computation
Mathematics - Commutative Algebra
030104 developmental biology
[SDV.BBM.MN] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular Networks [q-bio.MN]
Graph Theory
Linear algebra
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing-SYNASC 2020, 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing-SYNASC 2020, Sep 2020, Timisoara/Virtual, Romania, SYNASC
- Accession number :
- edsair.doi.dedup.....07ddf127ddfaecc37673d188d31baa20
- Full Text :
- https://doi.org/10.48550/arxiv.2010.12615