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A theoretical framework to analyse the flow of particles in a dynamical system with stochastic transition rates and site capacities

Title data

Jain, Aditi ; Kumar, Arun ; Gupta, Arvind Kumar:
A theoretical framework to analyse the flow of particles in a dynamical system with stochastic transition rates and site capacities.
In: Royal Society Open Science. Vol. 9 (2022) Issue 10 . - 220698.
ISSN 2054-5703
DOI: https://doi.org/10.1098/rsos.220698

Review:

Project information

Project financing: Andere
DST-SERB, Government of India (grants CRG/2019/004669 and MTR/2019/000312)

Abstract in another language

We study the stochasticity in a dynamical model: ribosome flow model with different site sizes that models the unidirectional movement of particles controlled by transition rates along a lattice having different site sizes. Our work models the parameters as random variables with known distributions and investigates the steady-state flow rate under this notion by using tools from the random matrix theory. Some closed-form theoretical results are derived for the steady-state flow rate under some restrictive assumptions such as random variables being independent and identically distributed. Furthermore, for arbitrary but bounded stochastic transition rates, stochastic site capacities, or both, we establish bounds for the steady-state flow rate. Our analysis can be generalized and applied to study the flow of particles in numerous transport systems in the stochastic environment.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: ribosome flow model with different site sizes; stochasticity; random variables; random matrix theory
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics)
Profile Fields > Advanced Fields > Nonlinear Dynamics
Research Institutions > Central research institutes > Bayreuth Research Center for Modeling and Simulation - MODUS
Result of work at the UBT: No
DDC Subjects: 500 Science > 510 Mathematics
500 Science > 570 Life sciences, biology
Date Deposited: 07 Mar 2025 11:42
Last Modified: 07 Mar 2025 11:42
URI: https://eref.uni-bayreuth.de/id/eprint/92619