Vorhersage von RNA-RNA Interaktionen durch kinetische Modellierung.

• Antragsteller: Professor Dr. Rolf Backofen
• Fachliche Zuordnung: Bioinformatik und Theoretische Biologie
• Förderung: Förderung von 2016 bis 2021
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 312982092

• Erstellungsjahr: 2022

Zusammenfassung der Projektergebnisse

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.

Projektbezogene Publikationen (Auswahl)

• 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
  
• 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.
  
• 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
  
• 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
  
• 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
  
• 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
  
• 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
  
• 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
  
• 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