BioinformaticsBioinformaticsPeer-reviewed journal article
Integration of accessibility data from structure probing into RNA-RNA interaction prediction
Milad MiladiiD, Soheila Montaseri, Rolf BackofeniD, Martin RadeniD
Abstract
SummaryExperimental structure probing data has been shown to improve thermodynamics-based RNA secondary structure prediction. To this end, chemical reactivity information (as provided e.g. by SHAPE) is incorporated, which encodes whether or not individual nucleotides are involved in intra-molecular structure. Since inter-molecular RNA-RNA interactions are often confined to unpaired RNA regions, SHAPE data is even more promising to improve interaction prediction. Here we show how 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 a spliceosomal U1 snRNA transcript with its target splice sites. When SHAPE data is incorporated, known target sites are predicted with increased precision and specificity.\n\nAvailabilityhttps://github.com/BackofenLab/IntaRNA
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: statistical model
- Citations
- 14
- FWCI
- 0.80
- Field percentile
- top 30%
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