Evidence map›Paper›PMID 31073612›Full record

ArticleNucleic acids research2019

The RNA workbench 2.0: next generation RNA data analysis.

Jörg Fallmann, Pavankumar Videm, Andrea Bagnacani, Bérénice Batut, Maria A Doyle, Tomas Klingstrom, Florian Eggenhofer, Peter F Stadler, Rolf Backofen, Björn Grüning

Abstract read
In one paragraph

Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. World journal of gastroenterology · 2025
    Article
  4. Evolutionary Structure Conservation and Covariance Scores.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Micro-RNA-RegulatedPlants (Basel, Switzerland) · 2022
    Article
  11. Review
  12. Article
  13. Article
  14. Dataset forData in brief · 2020
    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

10 authors.

Jörg FallmannBioinformatics Group, Department of Computer Science; Leipzig University, Härtelstraße 16-18, D-04107 Leipzig.
Pavankumar VidemBioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Georges-Köhler-Allee 106, Freiburg 79110, Germany.
Andrea BagnacaniDepartment of Systems Biology and Bioinformatics, Institute of Computer Science, University of Rostock, Ulmenstr. 69, 18057 Rostock, Germany.
Bérénice BatutBioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Georges-Köhler-Allee 106, Freiburg 79110, Germany.
Maria A DoyleResearch Computing Facility, Peter MacCallum Cancer Centre, Melbourne, Victoria 3000, Australia.
Tomas KlingstromSLU-Global Bioinformatics Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences.
Florian EggenhoferBioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Georges-Köhler-Allee 106, Freiburg 79110, Germany.
Peter F StadlerBioinformatics Group, Department of Computer Science; Leipzig University, Härtelstraße 16-18, D-04107 Leipzig.
Rolf BackofenBioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Georges-Köhler-Allee 106, Freiburg 79110, Germany.
Björn GrüningBioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Georges-Köhler-Allee 106, Freiburg 79110, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA has become one of the major research topics in molecular biology. As a central player in key processes regulating gene expression, RNA is in the focus of many efforts to decipher the pathways that govern the transition of genetic information to a fully functional cell. As more and more researchers join this endeavour, there is a rapidly growing demand for comprehensive collections of tools that cover the diverse layers of RNA-related research. However, increasing amounts of data, from diverse types of experiments, addressing different aspects of biological questions need to be consolidated and integrated into a single framework. Only then is it possible to connect findings from e.g. RNA-Seq experiments and methods for e.g. target predictions. To address these needs, we present the RNA Workbench 2.0 , an updated online resource for RNA related analysis. With the RNA Workbench we created a comprehensive set of analysis tools and workflows that enables researchers to analyze their data without the need for sophisticated command-line skills. This update takes the established framework to the next level, providing not only a containerized infrastructure for analysis, but also a ready-to-use platform for hands-on training, analysis, data exploration, and visualization. The new framework is available at https://rna.usegalaxy.eu , and login is free and open to all users. The containerized version can be found at https://github.com/bgruening/galaxy-rna-workbench.

Indexed as

SoftwareHigh-Throughput Nucleotide SequencingRNASequence Analysis, RNARNA

Identifiers

PMID31073612
PMCPMC6602469

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.