PT  - JOURNAL ARTICLE
AU  - Milad Miladi
AU  - Soheila Montaseri
AU  - Rolf Backofen
AU  - Martin Raden
TI  - Structure probing data enhances RNA-RNA interaction prediction
AID  - 10.1101/359323
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 359323
4099  - http://biorxiv.org/content/early/2018/06/29/359323.short
4100  - http://biorxiv.org/content/early/2018/06/29/359323.full
AB  - Summary Structure probing data has been shown to improve thermodynamics-based RNA structure prediction. However, this type of data has not been used to improve the prediction of RNA-RNA interactions. This is even more promising as the type of information (chemical reactivity as provided by SHAPE) is closely tied to the accessibility of nucleotides, which is an essential part for scoring RNA-RNA interactions. Here we show how that such experimental data can be incorporated seamlessly into accessibility-based RNA-RNA interaction prediction approaches, as implemented in IntaRNA. This is possible via the computation and use of unpaired probabilities that incorporate the structure probing information. We show that experimental SHAPE data can significantly improve RNA-RNA interaction prediction. We evaluate our approach by investigating interactions of the spliceosomal U1 RNA with its target splice sites. When SHAPE data is used, known target sites are predicted with increased precision and specificity.Availability https://github.com/BackofenLab/IntaRNASupplementary material https://github.com/BackofenLab/IntaRNA-benchmark-SHAPEContact mmann{at}informatik.uni-freiburg.de, backofen{at}informatik.uni-freiburg.de