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Aggregates of Monotonic Step Response systems : a structural classification

Blanchini, Franco; Cuba Samaniego, Christian; Franco, Elisa and Giordano, Giulia LU (2017) In IEEE Transactions on Control of Network Systems
Abstract

Complex dynamical networks can often be analysed as the interconnection of subsystems, to simplify the model and better understand the global behaviour. Some biological networks can be analysed as aggregates of monotone subsystems. Yet, monotonicity is a strong requirement and relies on the knowledge of an explicit state model. Systems with a Monotonic Step Response (MSR), which include input-output monotone systems, are a broader class and have interesting features. The property of having a monotonically increasing step response can be evinced from experimental data. We consider networks that can be decomposed as aggregates of MSR subsystems and we provide a structural (parameter-free) classification of oscillatory and multistationary... (More)

Complex dynamical networks can often be analysed as the interconnection of subsystems, to simplify the model and better understand the global behaviour. Some biological networks can be analysed as aggregates of monotone subsystems. Yet, monotonicity is a strong requirement and relies on the knowledge of an explicit state model. Systems with a Monotonic Step Response (MSR), which include input-output monotone systems, are a broader class and have interesting features. The property of having a monotonically increasing step response can be evinced from experimental data. We consider networks that can be decomposed as aggregates of MSR subsystems and we provide a structural (parameter-free) classification of oscillatory and multistationary behaviours. The classification is based on the exclusive or concurrent presence of negative and positive cycles in the system <formula><tex>$aggregate graph$</tex></formula>, whose nodes are the MSR subsystems. The result is analogous to our earlier classification for aggregates of monotone subsystems. Our classification is applied to models of biomolecular networks and helps build synthetic biomolecular circuits that, by design, are well suited to exhibit the desired dynamics.

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organization
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Contribution to journal
publication status
in press
subject
keywords
Aggregates, Analytical models, Biological system modeling, Integrated circuit interconnections, Jacobian matrices, Linear systems, Mathematical model
in
IEEE Transactions on Control of Network Systems
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85028721322
  • scopus:85028721322
ISSN
2325-5870
DOI
10.1109/TCNS.2017.2746343
language
English
LU publication?
yes
id
6f79ab6f-1e3c-4a79-809b-0e15ccee937e
date added to LUP
2017-08-22 11:29:45
date last changed
2018-01-07 12:15:37
@article{6f79ab6f-1e3c-4a79-809b-0e15ccee937e,
  abstract     = {<p>Complex dynamical networks can often be analysed as the interconnection of subsystems, to simplify the model and better understand the global behaviour. Some biological networks can be analysed as aggregates of monotone subsystems. Yet, monotonicity is a strong requirement and relies on the knowledge of an explicit state model. Systems with a Monotonic Step Response (MSR), which include input-output monotone systems, are a broader class and have interesting features. The property of having a monotonically increasing step response can be evinced from experimental data. We consider networks that can be decomposed as aggregates of MSR subsystems and we provide a structural (parameter-free) classification of oscillatory and multistationary behaviours. The classification is based on the exclusive or concurrent presence of negative and positive cycles in the system &lt;formula&gt;&lt;tex&gt;$aggregate graph$&lt;/tex&gt;&lt;/formula&gt;, whose nodes are the MSR subsystems. The result is analogous to our earlier classification for aggregates of monotone subsystems. Our classification is applied to models of biomolecular networks and helps build synthetic biomolecular circuits that, by design, are well suited to exhibit the desired dynamics.</p>},
  author       = {Blanchini, Franco and Cuba Samaniego, Christian and Franco, Elisa and Giordano, Giulia},
  issn         = {2325-5870},
  keyword      = {Aggregates,Analytical models,Biological system modeling,Integrated circuit interconnections,Jacobian matrices,Linear systems,Mathematical model},
  language     = {eng},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Transactions on Control of Network Systems},
  title        = {Aggregates of Monotonic Step Response systems : a structural classification},
  url          = {http://dx.doi.org/10.1109/TCNS.2017.2746343},
  year         = {2017},
}