Prediction of RNA-RNA Interactions by Kinetic Modelling
Final Report Abstract
RNA molecules are involved in a variety of regulatory processes in cells. Here, the direct interaction between two or more RNA molecules plays an important role. Therefore, the experimental determination and computational prediction as well as the investigation of such RNA-RNA interactions are important steps to understand the complex interactions of cellular processes. In this project, several bioinformatics approaches were novel and further developed to improve the accuracy and reliability of RNA-RNA interaction prediction. Theoretical models, e.g. from three-dimensional modelling, as well as experimental data were incorporated. The resulting software solutions are available for sustainable further use as open-source projects and were partly integrated into free web service and workflow systems. Thus, the results of this project directly form another cornerstone for the upcoming precise bioinformatic analysis of RNA-RNA interactions.
Publications
- IntaRNA 2.0: enhanced and customizable prediction of RNA-RNA interactions. Nucleic Acids Research, 45 no. W1 pp. W435-W439, 2017
Martin Mann, Patrick R. Wright, and Rolf Backofen
(See online at https://doi.org/10.1093/nar/gkx279) - Freiburg RNA tools: a central online resource for RNA- focused research and teaching. Nucleic Acids Research, 46 no. W1 pp. W25-W29, 2018
Martin Raden and Rolf Backofen et al.
(See online at https://doi.org/10.1093/nar/gky329) - 3D based on 2D: Calculating helix angles and stacking patterns using forgi 2.0, an RNA Python library centered on secondary structure elements, F1000Research, 8:287, 2019
Bernhard C. Thiel, Irene K. Beckmann, Ivo L. Hofacker
(See online at https://doi.org/10.12688/f1000research.18458.2) - IntaRNAhelix - composing RNA-RNA interactions from stable inter-molecular helices boosts bacterial sRNA target prediction. Journal of Bioinformatics and Computational Biology, 17 no. 5 pp. 1940009, 2019
Rick Gelhausen, Sebastian Will, Ivo L. Hofacker, Rolf Backofen, and Martin Raden
(See online at https://doi.org/10.1142/S0219720019400092) - Integration of accessibility data from structure probing into RNA-RNA interaction prediction. Bioinformatics, 35 no. 16 pp. 2862-2864, 2019
Milad Miladi, Soheila Montaseri, Rolf Backofen, and Martin Raden
(See online at https://doi.org/10.1093/bioinformatics/bty1029) - ShaKer: RNA SHAPE prediction using graph kernel. Bioinformatics, 35 no. 14 pp. i354-i359, 07 2019
Stefan Mautner, Soheila Montaseri, Milad Miladi, Martin Raden, Fabrizio Costa, and Rolf Backofen
(See online at https://doi.org/10.1093/bioinformatics/btz395) - CopomuS - ranking compensatory mutations to guide RNA-RNA interaction verification experiments. International Journal of Molecular Sciences, 21 no. 11 pp. 3852, 2020
Martin Raden, Fabio Gutmann, Michael Uhl, and Rolf Backofen
(See online at https://doi.org/10.3390/ijms21113852) - pourRNA - a time- and memory-efficient approach for the guided exploration of RNA energy landscapes. Bioinformatics, 36 no. 2 pp. 462-469, 2020
Gregor Entzian and Martin Raden
(See online at https://doi.org/10.1093/bioinformatics/btz583) - The impact of various seed, accessibility and interaction constraints on sRNA target prediction - a systematic as- sessment. BMC Bioinformatics, 21 pp. 15, 2020
Martin Raden, Teresa Müller, Stefan Mautner, Rick Gelhausen, and Rolf Backofen
(See online at https://doi.org/10.1186/s12859-019-3143-4)
