Evidence map›Paper›PMID 41119989›Full record

ArticleJournal of the Royal Society, Interface2025

Negative feedback and oscillations in a model for mRNA translation.

Aliza Ehrman, Thomas Kriecherbauer, Lars Grüne, Michael Margaliot

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Aliza EhrmanElectrical Engineering-Systems, Tel Aviv University, Tel Aviv-Yafo, Tel Aviv District, Israel.
Thomas KriecherbauerMathematics Institute, Universitat Bayreuth, Bayreuth, Bayern, Germany.
Lars GrüneMathematics Institute, Universitat Bayreuth, Bayreuth, Bayern, Germany.
Michael MargaliotElectrical Engineering-Systems, Tel Aviv University, Tel Aviv-Yafo, Tel Aviv District, Israel.ORCID 0000-0001-8319-8996

Funding

Deutsche ForschungsgemeinschaftIsrael Science Foundation
6 · The paper itself

Abstract

The ribosome flow model (RFM) is a phenomenological model for the unidirectional flow of particles along a one-dimensional chain of [Formula: see text] sites. The RFM has been extensively used to study the dynamics of ribosome flow along a single-mRNA molecule during translation. In this case, the particles model ribosomes and each site corresponds to a consecutive group of codons. Networks of interconnected RFMs have been used to model and analyse large-scale translation in the cell and, in particular, the effects of competition for shared resources. Here, we analyse the RFM with a negative feedback connection from the protein production rate to the initiation rate. This model is based on, for example, the production of proteins that inhibit the translation of their own mRNA. The RFM with negative feedback is a 2-cooperative dynamic system, i.e. its flow maps the set of vectors with up to one-sign variation to itself. Using tools from the theory of 2-cooperative dynamical systems, we provide a simple condition guaranteeing that the closed-loop system admits at least one non-trivial periodic solution. When this condition holds, we also explicitly characterize a large set of initial conditions such that any solution emanating from this set converges to a non-trivial periodic solution. Such a solution corresponds to a periodic pattern of ribosome densities along the mRNA and to a periodic pattern of protein production.

Indexed as

Feedback, PhysiologicalModels, BiologicalModels, GeneticProtein BiosynthesisRibosomesRNA, MessengerRNA, MessengermRNA translationperiodic solutionsregulation of gene expression

Identifiers

PMID41119989
PMCPMC12539956

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.