Evidence map›Paper›PMID 28977416›Full record

ArticleNucleic acids research2018

IMOTA: an interactive multi-omics tissue atlas for the analysis of human miRNA-target interactions.

Valeria Palmieri, Christina Backes, Nicole Ludwig, Tobias Fehlmann, Fabian Kern, Eckart Meese, Andreas Keller

Abstract read
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Construction and Analysis of miRNA Regulatory Networks.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  2. Article
  3. Article
  4. AmiCa: Atlas of miRNA-gene correlations in cancer.Computational and structural biotechnology journal · 2024
    Article
  5. Article
  6. Review
  7. Article
  8. MicroRNA Regulatory Network Analysis Using miRNet 2.0.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  9. Bioinformatics andInternational journal of ophthalmology · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Gastric Cancer MicroRNAs Meta-signature.International journal of molecular and cellular medicine · 2019
    Review
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

7 authors.

Valeria PalmieriChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
Christina BackesChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
Nicole LudwigDepartment for Human Genetics, Saarland University, 66424 Homburg, Germany.
Tobias FehlmannChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
Fabian KernChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
Eckart MeeseDepartment for Human Genetics, Saarland University, 66424 Homburg, Germany.
Andreas KellerChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Web repositories for almost all 'omics' types have been generated-detailing the repertoire of representatives across different tissues or cell types. A logical next step is the combination of these valuable sources. With IMOTA (interactive multi omics tissue atlas), we developed a database that includes 23 725 relations between miRNAs and 23 tissues, 310 932 relations between mRNAs and the same tissues as well as 63 043 relations between proteins and the 23 tissues in Homo sapiens. IMOTA also contains data on tissue-specific interactions, e.g. information on 331 413 miRNAs and target gene pairs that are jointly expressed in the considered tissues. By using intuitive filter and visualization techniques, it is with minimal effort possible to answer various questions. These include rather general questions but also requests specific for genes, miRNAs or proteins. An example for a general task could be 'identify all miRNAs, genes and proteins in the lung that are highly expressed and where experimental evidence proves that the miRNAs target the genes'. An example for a specific request for a gene and a miRNA could for example be 'In which tissues is miR-34c and its target gene BCL2 expressed?'. The IMOTA repository is freely available online at https://ccb-web.cs.uni-saarland.de/imota/.

Indexed as

Computational BiologyDatabases, GeneticGene Expression RegulationEpigenomicsForecastingGenome, HumanHigh-Throughput Screening AssaysHumansMicroRNAsOrgan SpecificityMicroRNAs

Identifiers

PMID28977416
PMCPMC5753248

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.