Evidence map›Paper›PMID 33790340›Full record

ArticleScientific reports2021

An R package for generic modular response analysis and its application to estrogen and retinoic acid receptor crosstalk.

Gabriel Jimenez-Dominguez, Patrice Ravel, Stéphan Jalaguier, Vincent Cavaillès, Jacques Colinge

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 24% of its field
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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

5 authors at 3 institutions in 1 country.

Gabriel Jimenez-DominguezInserm U1194, Institut de Recherche en Cancérologie de Montpellier, Montpellier, France.
Patrice RavelInserm U1194, Institut de Recherche en Cancérologie de Montpellier, Montpellier, France.
Stéphan JalaguierInserm U1194, Institut de Recherche en Cancérologie de Montpellier, Montpellier, France.
Vincent CavaillèsInserm U1194, Institut de Recherche en Cancérologie de Montpellier, Montpellier, France. vincent.cavailles@inserm.fr.
Jacques ColingeInserm U1194, Institut de Recherche en Cancérologie de Montpellier, Montpellier, France. jacques.colinge@inserm.fr.
Inserm · FRInstitut de Recherche en Cancérologie de Montpellier · FRUniversité de Montpellier · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modular response analysis (MRA) is a widely used inference technique developed to uncover directions and strengths of connections in molecular networks under a steady-state condition by means of perturbation experiments. We devised several extensions of this methodology to search genomic data for new associations with a biological network inferred by MRA, to improve the predictive accuracy of MRA-inferred networks, and to estimate confidence intervals of MRA parameters from datasets with low numbers of replicates. The classical MRA computations and their extensions were implemented in a freely available R package called aiMeRA ( https://github.com/bioinfo-ircm/aiMeRA/ ). We illustrated the application of our package by assessing the crosstalk between estrogen and retinoic acid receptors, two nuclear receptors implicated in several hormone-driven cancers, such as breast cancer. Based on new data generated for this study, our analysis revealed potential cross-inhibition mediated by the shared corepressors NRIP1 and LCoR. We designed aiMeRA for non-specialists and to allow biologists to perform their own analyses.

Indexed as

AlgorithmsBreast NeoplasmsGene Regulatory NetworksNeoplasm ProteinsReceptors, Retinoic AcidSoftwareFemaleHumansNeoplasm ProteinsReceptors, Retinoic Acid

Identifiers

PMID33790340
PMCPMC8012374
OpenAlexW3148252621

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.