Evidence map›Paper›PMID 33849334›Full record

ArticleJournal of the Royal Society, Interface2021

Quasi-robust control of biochemical reaction networks via stochastic morphing.

Tomislav Plesa, Guy-Bart Stan, Thomas E Ouldridge, Wooli Bae

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Tomislav PlesaDepartment of Bioengineering, Imperial College London, Exhibition Road, London SW7 2AZ, UK.
Guy-Bart StanDepartment of Bioengineering, Imperial College London, Exhibition Road, London SW7 2AZ, UK.
Thomas E OuldridgeDepartment of Bioengineering, Imperial College London, Exhibition Road, London SW7 2AZ, UK.
Wooli BaeDepartment of Bioengineering, Imperial College London, Exhibition Road, London SW7 2AZ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the main objectives of synthetic biology is the development of molecular controllers that can manipulate the dynamics of a given biochemical network that is at most partially known. When integrated into smaller compartments, such as living or synthetic cells, controllers have to be calibrated to factor in the intrinsic noise. In this context, biochemical controllers put forward in the literature have focused on manipulating the mean (first moment) and reducing the variance (second moment) of the target molecular species. However, many critical biochemical processes are realized via higher-order moments, particularly the number and configuration of the probability distribution modes (maxima). To bridge the gap, we put forward the

Indexed as

Models, BiologicalSynthetic BiologyAlgorithmsProbabilityStochastic ProcessescontrolDNA computingrobustnessstochastic biochemical reaction networkssynthetic biologytimescale separation

Identifiers

PMID33849334
PMCPMC8086924

What OpenQuestion holds

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Registered trials

None linked

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.