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Updated: Dec 31, 2025

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
Published on: December 1, 2023
The impact of various seed, accessibility and interaction constraints on sRNA target prediction- a systematic
Martin Raden1, Teresa Müller2, Stefan Mautner2
1Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, Freiburg, 79110, Germany. mann@informatik.uni-freiburg.de.
Background:
Seed and accessibility constraints are core features to enable highly accurate sRNA target screens based on RNA-RNA interaction prediction. Currently, available tools provide different (sets of) constraints and default parameter sets. Thus, it is hard to impossible for users to estimate the influence of individual restrictions on the prediction results.
Results:
Here, we present a systematic assessment of the impact of established and new constraints on sRNA target prediction both on a qualitative as well as computational level. This is done exemplarily based on the performance of IntaRNA, one of the most exact sRNA target prediction tools. IntaRNA provides various ways to constrain considered seed interactions, e.g. based on seed length, its accessibility, minimal unpaired probabilities, or energy thresholds, beside analogous constraints for the overall interaction. Thus, our results reveal the impact of individual constraints and their combinations.
Conclusions:
This provides both a guide for users what is important and recommendations for existing and upcoming sRNA target prediction approaches.We show on a large sRNA target screen benchmark data set that only by altering the parameter set, IntaRNA recovers 30% more verified interactions while becoming 5-times faster. This exemplifies the potential of seed, accessibility and interaction constraints for sRNA target prediction.
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