Negative feedback enables structurally signed steady-state influences in artificial biomolecular networks
(2016) 55th IEEE Conference on Decision and Control 2016 p.3369-3374- Abstract
We examine the capacity of artificial biomolecular networks to respond to perturbations with structurally signed steady-state changes. We consider network architectures designed to balance their output production as a function of downstream demand: the species producing the output, called a source, up- or down-regulates its production rate as a function of the demand. Using an exact algorithm we show that, in certain negative feedback architectures, changes in the total source concentration cause structurally signed variations of the steady-state output concentration, regardless of reaction rate parameters. Conversely, positive feedback schemes can exhibit the same signed behaviour for reasonable (but not for arbitrary) values of the... (More)
We examine the capacity of artificial biomolecular networks to respond to perturbations with structurally signed steady-state changes. We consider network architectures designed to balance their output production as a function of downstream demand: the species producing the output, called a source, up- or down-regulates its production rate as a function of the demand. Using an exact algorithm we show that, in certain negative feedback architectures, changes in the total source concentration cause structurally signed variations of the steady-state output concentration, regardless of reaction rate parameters. Conversely, positive feedback schemes can exhibit the same signed behaviour for reasonable (but not for arbitrary) values of the parameters. Numerical simulations demonstrate how the steady-state concentrations of different network architectures vary, responding to perturbations in total source amounts, consistently with our structural previsions.
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- author
- Giordano, Giulia LU and Franco, Elisa
- organization
- publishing date
- 2016-12-27
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2016 IEEE 55th Conference on Decision and Control, CDC 2016
- article number
- 7798776
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 55th IEEE Conference on Decision and Control 2016
- conference location
- Las Vegas, NV, United States
- conference dates
- 2016-09-12 - 2016-09-14
- external identifiers
-
- scopus:85010764207
- ISBN
- 9781509018376
- DOI
- 10.1109/CDC.2016.7798776
- language
- English
- LU publication?
- yes
- id
- 9ebcee37-63bd-4cc5-8cac-805af70f657d
- date added to LUP
- 2017-01-10 11:35:01
- date last changed
- 2022-03-01 18:37:17
@inproceedings{9ebcee37-63bd-4cc5-8cac-805af70f657d,
abstract = {{<p>We examine the capacity of artificial biomolecular networks to respond to perturbations with structurally signed steady-state changes. We consider network architectures designed to balance their output production as a function of downstream demand: the species producing the output, called a source, up- or down-regulates its production rate as a function of the demand. Using an exact algorithm we show that, in certain negative feedback architectures, changes in the total source concentration cause structurally signed variations of the steady-state output concentration, regardless of reaction rate parameters. Conversely, positive feedback schemes can exhibit the same signed behaviour for reasonable (but not for arbitrary) values of the parameters. Numerical simulations demonstrate how the steady-state concentrations of different network architectures vary, responding to perturbations in total source amounts, consistently with our structural previsions.</p>}},
author = {{Giordano, Giulia and Franco, Elisa}},
booktitle = {{2016 IEEE 55th Conference on Decision and Control, CDC 2016}},
isbn = {{9781509018376}},
language = {{eng}},
month = {{12}},
pages = {{3369--3374}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Negative feedback enables structurally signed steady-state influences in artificial biomolecular networks}},
url = {{http://dx.doi.org/10.1109/CDC.2016.7798776}},
doi = {{10.1109/CDC.2016.7798776}},
year = {{2016}},
}