Simulation strategy of membrane computing to characterize the structure and non-deterministic behavior of biological systems

A case study with ligand-receptor network of protein TGF-β

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The processes in biological systems evolve in discrete and non-deterministic ways. Simulation of conventional models such as ordinary differential equations with continuous and deterministic evolution strategy has disregarded those behaviors in biological systems. Membrane computing which has been applied in a nondeterministic and maximally parallel way to capture the structure and behaviors of biological systems could be used to address the limitations in ordinary differential equations. The stochastic simulation strategy based on Gillespie's algorithm has been used to simulate membrane computing model. This study was carried out to demonstrate the capability of membrane computing model in characterizing the structure and behaviors of biological systems in comparison to the model of ordinary differential equations. The results demonstrated that the simulation of membrane computing model preserves the structure and non-deterministic behaviors of biological systems that ignored in the ordinary differential equations model.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages56-66
Number of pages11
Volume7066 LNCS
EditionPART 1
DOIs
Publication statusPublished - 2011
Event2nd International Visual Informatics Conference, IVIC 2011 - Selangor
Duration: 9 Nov 201111 Nov 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7066 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd International Visual Informatics Conference, IVIC 2011
CitySelangor
Period9/11/1111/11/11

Fingerprint

Membrane Computing
Biological systems
Biological Systems
Receptor
Ligands
Proteins
Membranes
Protein
Ordinary differential equations
Ordinary differential equation
Simulation
Model
Evolution Strategies
Stochastic Simulation
Strategy
Demonstrate

Keywords

  • biological systems
  • Membrane computing
  • stochastic simulation

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Muniyandi, R. C., & Mohd. Zin, A. (2011). Simulation strategy of membrane computing to characterize the structure and non-deterministic behavior of biological systems: A case study with ligand-receptor network of protein TGF-β. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 7066 LNCS, pp. 56-66). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7066 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-25191-7_7

Simulation strategy of membrane computing to characterize the structure and non-deterministic behavior of biological systems : A case study with ligand-receptor network of protein TGF-β. / Muniyandi, Ravie Chandren; Mohd. Zin, Abdullah.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7066 LNCS PART 1. ed. 2011. p. 56-66 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7066 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Muniyandi, RC & Mohd. Zin, A 2011, Simulation strategy of membrane computing to characterize the structure and non-deterministic behavior of biological systems: A case study with ligand-receptor network of protein TGF-β. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 7066 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7066 LNCS, pp. 56-66, 2nd International Visual Informatics Conference, IVIC 2011, Selangor, 9/11/11. https://doi.org/10.1007/978-3-642-25191-7_7
Muniyandi RC, Mohd. Zin A. Simulation strategy of membrane computing to characterize the structure and non-deterministic behavior of biological systems: A case study with ligand-receptor network of protein TGF-β. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 7066 LNCS. 2011. p. 56-66. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-25191-7_7
Muniyandi, Ravie Chandren ; Mohd. Zin, Abdullah. / Simulation strategy of membrane computing to characterize the structure and non-deterministic behavior of biological systems : A case study with ligand-receptor network of protein TGF-β. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7066 LNCS PART 1. ed. 2011. pp. 56-66 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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