Evidence map›Paper›PMID 26304616›Full record

ArticleJournal of mathematical biology2016

Scale invariance analysis for genetic networks applying homogeneity.

Emmanuel Bernuau, Denis Efimov, Wilfrid Perruquetti

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In one paragraph

Article in Journal of mathematical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

3 authors.

Emmanuel BernuauFaculty of Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy.
Denis EfimovNon-A Team, Inria Lille, Parc Scientifique de la Haute Borne, 40 avenue Halley, 59650, Villeneuve d'Ascq, France. efde@mail.ru.
Wilfrid PerruquettiNon-A Team, Inria Lille, Parc Scientifique de la Haute Borne, 40 avenue Halley, 59650, Villeneuve d'Ascq, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Scalability is a property describing the change of the trajectory of a dynamical system under a scaling of the input stimulus and of the initial conditions. Particular cases of scalability include the scale invariance and fold change detection (when the scaling of the input does not influence the system output). In the present paper it is shown that homogeneous systems have this scalability property while locally homogeneous systems approximately possess this property. These facts are used for detecting scale invariance or approximate scalability (far from a steady state) in several biological systems. The results are illustrated by various regulatory networks.

Indexed as

Gene Regulatory NetworksModels, GeneticMathematical ConceptsModels, BiologicalSystems Biology34D2037C7537C8092D25

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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.