Publications (5)
Scalable Deep Learning for RNA Secondary Structure Prediction
Jörg K. H. Franke, Frederic Runge, Frank Hutter
The field of RNA secondary structure prediction has made significant progress with the adoption of deep learning techniques. In this work, we present the RNAformer, a lean deep lea…
Towards Automated Design of Riboswitches
Frederic Runge, Jörg K. H. Franke, Frank Hutter
Experimental screening and selection pipelines for the discovery of novel riboswitches are expensive, time-consuming, and inefficient. Using computational methods to reduce the num…
Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design
Jörg K. H. Franke, Frederic Runge, Frank Hutter
Our world is ambiguous and this is reflected in the data we use to train our algorithms. This is particularly true when we try to model natural processes where collected data is af…
Learning to Design RNA
Frederic Runge, Danny Stoll, Stefan Falkner +1
Designing RNA molecules has garnered recent interest in medicine, synthetic biology, biotechnology and bioinformatics since many functional RNA molecules were shown to be involved…
Rethinking Performance Measures of RNA Secondary Structure Problems
Frederic Runge, Jörg K. H. Franke, Daniel Fertmann +1
Accurate RNA secondary structure prediction is vital for understanding cellular regulation and disease mechanisms. Deep learning (DL) methods have surpassed traditional algorithms…