Evidence map›Paper›PMID 32179762›Full record

ArticleScientific reports2020

Hepamine - A Liver Disease Microarray Database, Visualization Platform and Data-Mining Resource.

Timo Itzel, Melanie Neubauer, Matthias Ebert, Matthias Evert, Andreas Teufel

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

5 authors.

Timo ItzelDivision of Hepatology, Department of Medicine II, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Melanie NeubauerDivision of Hepatology, Department of Medicine II, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Matthias EbertDepartment of Medicine II, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Matthias EvertDepartment of Pathology, University of Regensburg, Regensburg, Germany.
Andreas TeufelDivision of Hepatology, Department of Medicine II, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. andreas.teufel@medma.uni-heidelberg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous gene expression profiling data on liver diseases were generated and stored in public databases. Only few were used for additional analyses by the hepatology research community. This may mostly be due to limited bioinformatics knowledge of most biomedical research personnel. In order to support an easy translation of bioinformatics data into translational hepatology research, we created Hepamine, a liver disease gene expression, visualization platform and data-mining resource. Microarray data were obtained from the NCBI GEO database. Pre-analysis of expression data was performed using R statistical software and the limma microarray analysis package from the Bioconductor repository. We generated Hepamine, a web-based repository of pre-analyzed microarray data for various liver diseases. At its initial release Hepamine contains 13 gene expression datasets, 20 microarray experiments and approximately 400 000 gene expression measurements. A self-explanatory website offers open and easy access to gene expression profiles. Results are furthermore visualized in simple three-color tables indicating differential expression. All data were linked to common functional and genetic databases particularly through the DAVID bioinformatics suite. Hepamine provides comprehensive data and easy access to hepatologic gene expression data even without in depth bioinformatics or microarray profiling experience. http://www.hepamine.de.

Indexed as

Databases, GeneticData MiningDatasets as TopicGene ExpressionGene Expression ProfilingOligonucleotide Array Sequence AnalysisComputational BiologyHumansLiver DiseasesSoftwareTranslational Research, Biomedical

Identifiers

PMID32179762
PMCPMC7075926

What OpenQuestion holds

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Registered trials

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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.