Despite their complexity, biological systems are able to endure huge parameter fluctuations and survive in the most diverse environmental conditions. Mathematical tools from graph theory and systems and control theory are naturally well-suited to understand the functioning of biological systems and reveal that their tremendous robustness is often rooted in their peculiar interconnection structure. This survey considers a wide class of ordinary-differential-equation biological models, including chemical reaction networks, and provides an overview of structural approaches proposed in the literature to assess whether a system structure enjoys fundamental qualitative properties, yielding specific types of dynamic or steady-state behaviours, regardless of the precise parameter values.

Structural analysis in biology: A control-theoretic approach / Blanchini, Franco; Giordano, Giulia. - In: AUTOMATICA. - ISSN 0005-1098. - 126:(2021), pp. 109376.1-109376.23. [10.1016/j.automatica.2020.109376]

Structural analysis in biology: A control-theoretic approach

Giordano, Giulia
2021-01-01

Abstract

Despite their complexity, biological systems are able to endure huge parameter fluctuations and survive in the most diverse environmental conditions. Mathematical tools from graph theory and systems and control theory are naturally well-suited to understand the functioning of biological systems and reveal that their tremendous robustness is often rooted in their peculiar interconnection structure. This survey considers a wide class of ordinary-differential-equation biological models, including chemical reaction networks, and provides an overview of structural approaches proposed in the literature to assess whether a system structure enjoys fundamental qualitative properties, yielding specific types of dynamic or steady-state behaviours, regardless of the precise parameter values.
2021
Blanchini, Franco; Giordano, Giulia
Structural analysis in biology: A control-theoretic approach / Blanchini, Franco; Giordano, Giulia. - In: AUTOMATICA. - ISSN 0005-1098. - 126:(2021), pp. 109376.1-109376.23. [10.1016/j.automatica.2020.109376]
File in questo prodotto:
File Dimensione Formato  
2021_BG_Automatica_Survey.pdf

Solo gestori archivio

Descrizione: Articolo
Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.53 MB
Formato Adobe PDF
1.53 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/290361
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 10
  • ???jsp.display-item.citation.isi??? 10
social impact