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The impact of various seed, accessibility and interaction constraints on sRNA target prediction- a systematic assessment.

Martin RadenTeresa MüllerStefan MautnerRick GelhausenRolf Backofen
Published in: BMC bioinformatics (2020)
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.
Keyphrases
  • high throughput
  • clinical practice
  • risk assessment
  • big data
  • artificial intelligence
  • climate change
  • human health