@article{Raden-IntaRNA-benchmark-2019,
author={Martin Raden and Teresa M{\"u}ller and Stefan Mautner and Rick Gelhausen and Rolf Backofen},
title={The impact of various seed, accessibility and interaction constraints on {sRNA} target prediction - a systematic assessment},
journal={BMC Bioinformatics},
year={2020},
volume={21},
pages={15},
doi={10.1186/s12859-019-3143-4},
issn={1471-2105},
user={mmann},
abstract={
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.
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.
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 percent more verified interactions while becoming 5-times faster.
This exemplifies the potential of seed, accessibility and interaction constraints for sRNA target prediction.
}
}