Fully automated attractor analysis of cyanobacteria models

Benes, N; Brim, L; Pastva, S; Safranek, D; Trojak, M; Cerveny, J; Salagovic, J

Fully automated attractor analysis of cyanobacteria models

Benes, N Brim, L Pastva, S Safranek, D Trojak, M Cerveny, J

Salagovic, J

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Publication Type:: Conference Proceeding
Citation:: 2018 22nd International Conference on System Theory, Control and Computing, ICSTCC 2018 - Proceedings, 2018, pp. 354 - 359
Issue Date:: 2018-11-19

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Field	Value	Language
dc.contributor.author	Benes, N	en_US
dc.contributor.author	Brim, L	en_US
dc.contributor.author	Pastva, S	en_US
dc.contributor.author	Safranek, D	en_US
dc.contributor.author	Trojak, M	en_US
dc.contributor.author	Cerveny, J https://orcid.org/0000-0002-5046-3105	en_US
dc.contributor.author	Salagovic, J	en_US
dc.date.issued	2018-11-19	en_US
dc.identifier.citation	2018 22nd International Conference on System Theory, Control and Computing, ICSTCC 2018 - Proceedings, 2018, pp. 354 - 359	en_US
dc.identifier.isbn	9781538644447	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133862
dc.description.abstract	© 2018 IEEE. Complex dynamics arising in biological systems can be characterised by various kinds of attractors. To that end, the task of determining attractors becomes important in modern systems analysis. Biological systems are typically formalised as highly parametrised continuous-time ODE models. Such models can be abstracted in the form of parametrised graphs. In such abstractions, attractors are observed in the form of terminal strongly connected components (tSCCs). In this paper, we demonstrate a novel method for detecting tSCCs in parametrised graphs on several models of cyanobacteria taken from the domain-specific online platform e-cyanobacterium.org.	en_US
dc.relation.ispartof	2018 22nd International Conference on System Theory, Control and Computing, ICSTCC 2018 - Proceedings	en_US
dc.relation.isbasedon	10.1109/ICSTCC.2018.8540762	en_US
dc.title	Fully automated attractor analysis of cyanobacteria models	en_US
dc.type	Conference Proceeding
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. Complex dynamics arising in biological systems can be characterised by various kinds of attractors. To that end, the task of determining attractors becomes important in modern systems analysis. Biological systems are typically formalised as highly parametrised continuous-time ODE models. Such models can be abstracted in the form of parametrised graphs. In such abstractions, attractors are observed in the form of terminal strongly connected components (tSCCs). In this paper, we demonstrate a novel method for detecting tSCCs in parametrised graphs on several models of cyanobacteria taken from the domain-specific online platform e-cyanobacterium.org.

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