Detailed Information on Publication Record
2018
Fully Automated Attractor Analysis of Cyanobacteria Models
BENEŠ, Nikola, Luboš BRIM, Jan ČERVENÝ, Samuel PASTVA, David ŠAFRÁNEK et. al.Basic information
Original name
Fully Automated Attractor Analysis of Cyanobacteria Models
Name in Czech
Plne Automatizovaná Analýza Atraktorů Modelů Cyanobaktérií
Authors
BENEŠ, Nikola (203 Czech Republic, belonging to the institution), Luboš BRIM (203 Czech Republic, belonging to the institution), Jan ČERVENÝ (203 Czech Republic), Samuel PASTVA (703 Slovakia, belonging to the institution), David ŠAFRÁNEK (203 Czech Republic, belonging to the institution), Jakub ŠALAGOVIČ (703 Slovakia) and Matej TROJÁK (703 Slovakia, belonging to the institution)
Edition
Neuveden, 22nd International Conference on System Theory, Control and Computing, p. 354-359, 6 pp. 2018
Publisher
IEEE
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
printed version "print"
References:
RIV identification code
RIV/00216224:14330/18:00101265
Organization unit
Faculty of Informatics
ISBN
978-1-5386-4444-7
UT WoS
000465109800058
Keywords (in Czech)
atraktory; parametrizovaný graf; koncové silne souvislé komponenty; cyanobaktérie
Keywords in English
attractors; parametrised graph; terminal strongly connected components; cyanobacteria
Tags
Tags
International impact, Reviewed
Změněno: 13/5/2020 19:34, RNDr. Pavel Šmerk, Ph.D.
Abstract
V originále
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 demon- strate a novel method for detecting tSCCs in parametrised graphs on several models of cyanobacteria taken from the domain- specific online platform e-cyanobacterium.org.
Links
GA18-00178S, research and development project |
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LM2015055, research and development project |
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MUNI/A/0854/2017, interní kód MU |
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