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Exploiting Variable Sparsity in Computing Equilibria of Biological Dynamical Systems by Triangular Decomposition

  • Wenwen Ju
  • , Chenqi Mou*
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Biological systems modeled as dynamical systems can be large in the number of variables and sparse in the interrelationship between the variables. In this paper we exploit the variable sparsity of biological dynamical systems in computing their equilibria by using sparse triangular decomposition. The variable sparsity of a biological dynamical system is characterized via the associated graph constructed from the polynomial set in the system. To make use of sparse triangular decomposition which has been proven to maintain the variable sparsity when a perfect elimination ordering of a chordal associated graph is used, we first study the influence of chordal completion on the variable sparsity for a large number of biological dynamical systems. Then for those systems which are both large and sparse, we compare the computational performances of sparse triangular decomposition versus ordinary one with experiments. The experimental results verify the efficiency gains in sparse triangular decomposition exploiting the variable sparsity.

Original languageEnglish
Title of host publicationAlgorithms for Computational Biology - 8th International Conference, AlCoB 2021, Proceedings
EditorsCarlos Martín-Vide, Miguel A. Vega-Rodríguez, Travis Wheeler
PublisherSpringer Science and Business Media Deutschland GmbH
Pages29-41
Number of pages13
ISBN (Print)9783030744311
DOIs
StatePublished - 2021
Event8th International Conference on Algorithms for Computational Biology, AlCoB 2021 - Missoula, United States
Duration: 7 Jun 202111 Jun 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12715 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Algorithms for Computational Biology, AlCoB 2021
Country/TerritoryUnited States
CityMissoula
Period7/06/2111/06/21

Keywords

  • Biological dynamical system
  • Chordal completion
  • Equilibria
  • Systems biology
  • Triangular decomposition
  • Variable sparsity

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