Evidence map›Paper›PMID 27311961›Full record

ArticleEMBO molecular medicine2016

Defining the optimal animal model for translational research using gene set enrichment analysis.

Christopher Weidner, Matthias Steinfath, Elisa Opitz, Michael Oelgeschläger, Gilbert Schönfelder

Open access · goldAbstract read
In one paragraph

Article in EMBO molecular medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
5.4field-weighted citation impact, top 4% 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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 27 citations in OpenAlex.

  1. A Cross-Species and Sex-Specific Meta-Analysis of Transcriptomic Studies of Pulmonary Hypertension.American journal of respiratory cell and molecular biology · 2025
    Pooled it
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  5. Transcriptomic congruence analysis for evaluating model organisms.Proceedings of the National Academy of Sciences of the United States of America · 2023
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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 1 institution in 1 country.

Christopher WeidnerDepartment of Experimental Toxicology and ZEBET, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.
Matthias SteinfathDepartment of Experimental Toxicology and ZEBET, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.
Elisa OpitzDepartment of Experimental Toxicology and ZEBET, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.
Michael OelgeschlägerDepartment of Experimental Toxicology and ZEBET, German Federal Institute for Risk Assessment (BfR), Berlin, Germany.
Gilbert SchönfelderDepartment of Experimental Toxicology and ZEBET, German Federal Institute for Risk Assessment (BfR), Berlin, Germany Department of Clinical Pharmacology and Toxicology, Charité-Universitätsmedizin Berlin, Berlin, Germany gilbert.schoenfelder@bfr.bund.de.ORCID 0000-0001-6134-1990
Federal Institute for Risk Assessment · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mouse is the main model organism used to study the functions of human genes because most biological processes in the mouse are highly conserved in humans. Recent reports that compared identical transcriptomic datasets of human inflammatory diseases with datasets from mouse models using traditional gene-to-gene comparison techniques resulted in contradictory conclusions regarding the relevance of animal models for translational research. To reduce susceptibility to biased interpretation, all genes of interest for the biological question under investigation should be considered. Thus, standardized approaches for systematic data analysis are needed. We analyzed the same datasets using gene set enrichment analysis focusing on pathways assigned to inflammatory processes in either humans or mice. The analyses revealed a moderate overlap between all human and mouse datasets, with average positive and negative predictive values of 48 and 57% significant correlations. Subgroups of the septic mouse models (i.e., Staphylococcus aureus injection) correlated very well with most human studies. These findings support the applicability of targeted strategies to identify the optimal animal model and protocol to improve the success of translational research.

Indexed as

Disease Models, AnimalGene Regulatory NetworksAnimalsGene Expression ProfilingHumansMiceSepsisSystems BiologyTranslational Research, Biomedicalanimal modelGSEAinflammationtranscriptomicstranslational research

Identifiers

PMID27311961
PMCPMC4967938
OpenAlexW2440022739

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.