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Updated: Jun 25, 2025

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA
Published on: July 9, 2021
How to do RNA-RNA Interaction Prediction? A Use-Case Driven Handbook Using IntaRNA
1Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany. mmann@informatik.uni-freiburg.de.
Abstract:
Computational prediction of RNA-RNA interactions (RRI) is a central methodology for the specific investigation of inter-molecular RNA interactions and regulatory effects of non-coding RNAs like eukaryotic microRNAs or prokaryotic small RNAs. Available methods can be classified according to their underlying prediction strategies, each implicating specific capabilities and restrictions often not transparent to the non-expert user. Within this work, we review seven classes of RRI prediction strategies and discuss the advantages and limitations of respective tools, since such knowledge is essential for selecting the right tool in the first place.Among the RRI prediction strategies, accessibility-based approaches have been shown to provide the most reliable predictions. Here, we describe how IntaRNA, as one of the state-of-the-art accessibility-based tools, can be applied in various use cases for the task of computational RRI prediction. Detailed hands-on examples for individual RRI predictions as well as large-scale target prediction scenarios are provided. We illustrate the flexibility and capabilities of IntaRNA through the examples. Each example is designed using real-life data from the literature and is accompanied by instructions on interpreting the respective results from IntaRNA output. Our use-case driven instructions enable non-expert users to comprehensively understand and utilize IntaRNA's features for effective RRI predictions.
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