RNA secondary structure prediction with KNetFold

KNetFold is a new software for predicting the consensus secondary structure for a given alignment of RNA sequences. It uses an innovative classifier system (a hierarchical network of k-nearest neighbor classifiers) to compute for each pair of alignment positions a "base pair" or "no base pair" prediction.

We evaluated the accuracy of the KNetFold algorithm with a set of 49 RNA sequence alignments obtained from the RFAM database. In our recent publication, we show that for this test set, the performance of the method is higher compared to the programs PFOLD and RNAalifold. We also show, that the method is able to predict pseudoknots.

A web server for KNetFold project is currently available here. If you have any questions about this project, feel free to contact Eckart Bindewald.