Title data
Ofir, Ron ; Kriecherbauer, Thomas ; Grüne, Lars ; Margaliot, Michael:
On the gain of entrainment in the ndimensional ribosome flow model.
In: Interface : Journal of the Royal Society.
Vol. 20
(2023)
Issue 199
.
 20220763.
ISSN 17425662
DOI: https://doi.org/10.1098/rsif.2022.0763
This is the latest version of this item.
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Project information
Project title: 
Project's official title Project's id Analysis of Random Transport in Chains using Modern Tools from Systems and Control Theory GR 1569/241, KR 1673/71 

Project financing: 
Deutsche Forschungsgemeinschaft Israel Science Foundation Grants 
Abstract in another language
The ribosome flow model (RFM) is a phenomenological model for the flow of particles along a 1D chain of sites. It has been extensively used to study ribosome flow along the mRNA molecule during translation. When the transition rates along the chain are timevarying and jointly Tperiodic the RFM entrains, i.e., every trajectory of the RFM converges to a unique Tperiodic solution that depends on the transition rates, but not on the initial condition. Entrainment to periodic excitations like the 24h solar day or the 50Hz frequency of the electric grid is important in numerous natural and artificial systems. An interesting question, called the gain of entrainment (GOE), is whether proper coordination of the periodic translation rates along the mRNA can lead to a larger average protein production rate. Analyzing the GOE in the RFM is nontrivial and partial results exist only for the RFM with dimensions n=1, 2. We use a new approach to derive several results on the GOE in the general ndimensional RFM. Perhaps surprisingly, we rigorously characterize several cases where there is no GOE, so to maximize the average production rate in these cases, the best choice is to use constant transition rates along the chain.
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On the gain of entrainment in the ndimensional ribosome flow model. (deposited 24 Oct 2022 11:47)
 On the gain of entrainment in the ndimensional ribosome flow model. (deposited 24 Mar 2023 08:16) [Currently Displayed]