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Computational approaches for circular RNA analysis.

Tobias Jakobi1,2, Christoph Dieterich1,2

  • 1Section of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology and Department of Internal Medicine III (Cardiology, Angiology, and Pneumology), University Hospital Heidelberg, Heidelberg, Germany.

Wiley Interdisciplinary Reviews. RNA
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Summary
This summary is machine-generated.

Circular RNAs (circRNAs) are novel RNA molecules detected via complex computational analysis. This study reviews tools and validation strategies for circRNA research, aiding functional characterization.

Keywords:
RNA splicingbioinformaticscircular RNAsoftware

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Area of Science:

  • RNA Biology
  • Computational Biology
  • Genomics

Background:

  • Circular RNAs (circRNAs) are a class of RNA molecules formed by back-splicing.
  • Their expression is cell-type and developmental stage-specific.
  • Few circRNAs have been functionally characterized to date.

Purpose of the Study:

  • To provide an overview of computational analysis tools and pipelines for circRNA detection.
  • To outline common technical and experimental requirements and potential pitfalls.
  • To present validation strategies and resources for circRNA research.

Main Methods:

  • Review of existing computational analysis tools and pipelines for circRNA detection.
  • Discussion of in silico and in vitro validation strategies.
  • Presentation of pipelines for primary sequence delineation and function prediction.

Main Results:

  • Computational prediction of circRNAs has matured significantly.
  • Various tools and pipelines are available for circRNA detection and analysis.
  • Validation strategies and web resources are crucial for advancing circRNA research.

Conclusions:

  • Accurate computational detection and validation are essential for understanding circRNA function.
  • The reviewed resources and strategies facilitate circRNA research.
  • Further functional characterization of circRNAs is needed.