Literature DB >> 22732691

Stability analysis of the ribosome flow model.

Michael Margaliot1, Tamir Tuller.   

Abstract

Gene translation is a central process in all living organisms. Developing a better understanding of this complex process may have ramifications to almost every biomedical discipline. Recently, Reuveni et al. proposed a new computational model of this process called the ribosome flow model (RFM). In this study, we show that the dynamical behavior of the RFM is relatively simple. There exists a unique equilibrium point e and every trajectory converges to e. Furthermore, convergence is monotone in the sense that the distance to e can never increase. This qualitative behavior is maintained for any feasible set of parameter values, suggesting that the RFM is highly robust. Our analysis is based on a contraction principle and the theory of monotone dynamical systems. These analysis tools may prove useful in studying other properties of the RFM as well as additional intracellular biological processes.

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Year:  2012        PMID: 22732691     DOI: 10.1109/TCBB.2012.88

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  21 in total

1.  Ribosome flow model with positive feedback.

Authors:  Michael Margaliot; Tamir Tuller
Journal:  J R Soc Interface       Date:  2013-05-29       Impact factor: 4.118

2.  Maximizing protein translation rate in the non-homogeneous ribosome flow model: a convex optimization approach.

Authors:  Gilad Poker; Yoram Zarai; Michael Margaliot; Tamir Tuller
Journal:  J R Soc Interface       Date:  2014-11-06       Impact factor: 4.118

3.  A model for competition for ribosomes in the cell.

Authors:  Alon Raveh; Michael Margaliot; Eduardo D Sontag; Tamir Tuller
Journal:  J R Soc Interface       Date:  2016-03       Impact factor: 4.118

4.  Ribosome flow model with extended objects.

Authors:  Yoram Zarai; Michael Margaliot; Tamir Tuller
Journal:  J R Soc Interface       Date:  2017-10       Impact factor: 4.118

5.  A Modelling Framework Linking Resource-Based Stochastic Translation to the Optimal Design of Synthetic Constructs.

Authors:  Peter Sarvari; Duncan Ingram; Guy-Bart Stan
Journal:  Biology (Basel)       Date:  2021-01-07

6.  Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution.

Authors:  Hadas Zur; Tamir Tuller
Journal:  Nucleic Acids Res       Date:  2016-09-02       Impact factor: 16.971

7.  On the Ribosomal Density that Maximizes Protein Translation Rate.

Authors:  Yoram Zarai; Michael Margaliot; Tamir Tuller
Journal:  PLoS One       Date:  2016-11-18       Impact factor: 3.240

8.  Controllability Analysis and Control Synthesis for the Ribosome Flow Model.

Authors:  Yoram Zarai; Michael Margaliot; Eduardo D Sontag; Tamir Tuller
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2017-05-23       Impact factor: 3.710

9.  Large-scale mRNA translation and the intricate effects of competition for the finite pool of ribosomes.

Authors:  Aditi Jain; Michael Margaliot; Arvind Kumar Gupta
Journal:  J R Soc Interface       Date:  2022-03-09       Impact factor: 4.118

10.  Sensitivity of mRNA Translation.

Authors:  Gilad Poker; Michael Margaliot; Tamir Tuller
Journal:  Sci Rep       Date:  2015-08-04       Impact factor: 4.379

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