Evidence map›Paper›PMID 33328476›Full record

ArticleScientific data2020

A gene expression atlas for different kinds of stress in the mouse brain.

Tiziano Flati, Silvia Gioiosa, Giovanni Chillemi, Andrea Mele, Alberto Oliverio, Cecilia Mannironi, Arianna Rinaldi, Tiziana Castrignanò

Open access · goldAbstract read
In one paragraph

Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 5% 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

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.

  1. Pooled it
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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

8 authors at 4 institutions in 1 country.

Tiziano FlatiCINECA, SuperComputing Applications and Innovation Department, Via dei Tizii 6, 00185, Roma, Italy.
Silvia GioiosaCINECA, SuperComputing Applications and Innovation Department, Via dei Tizii 6, 00185, Roma, Italy.ORCID 0000-0003-1302-8320
Giovanni ChillemiDIBAF, University of Tuscia, 01100, Viterbo, Italy.
Andrea MeleDepartment of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Rome, Italy.
Alberto OliverioDepartment of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Rome, Italy.
Cecilia MannironiIstituto di Biologia e Patologia Molecolari, CNR, Rome, Italy.ORCID 0000-0001-6934-8425
Arianna RinaldiDepartment of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Rome, Italy. arianna.rinaldi@uniroma1.it.ORCID 0000-0002-5167-7420
Tiziana CastrignanòDepartment of Ecological and Biological Sciences (DEB), University of Tuscia, Largo Università snc, 01100, Viterbo, Italy. tiziana.castrignano@unitus.it.
Sapienza University of Rome · ITCineca · ITUniversità degli Studi della Tuscia · ITInstitute of Molecular Biology and Pathology · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stressful experiences are part of everyday life and animals have evolved physiological and behavioral responses aimed at coping with stress and maintaining homeostasis. However, repeated or intense stress can induce maladaptive reactions leading to behavioral disorders. Adaptations in the brain, mediated by changes in gene expression, have a crucial role in the stress response. Recent years have seen a tremendous increase in studies on the transcriptional effects of stress. The input raw data are freely available from public repositories and represent a wealth of information for further global and integrative retrospective analyses. We downloaded from the Sequence Read Archive 751 samples (SRA-experiments), from 18 independent BioProjects studying the effects of different stressors on the brain transcriptome in mice. We performed a massive bioinformatics re-analysis applying a single, standardized pipeline for computing differential gene expression. This data mining allowed the identification of novel candidate stress-related genes and specific signatures associated with different stress conditions. The large amount of computational results produced was systematized in the interactive "Stress Mice Portal".

Indexed as

Gene ExpressionStress, PhysiologicalStress, PsychologicalTranscriptomeAnimalsBrainComputational BiologyData MiningDatasets as TopicFemaleMaleMice

Identifiers

PMID33328476
PMCPMC7744580
OpenAlexW3111074515

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.