PT37: Michiaki Hamada - Predictions of RNA Secondary Structure by Combining Homologous Sequence Information
Need for better RNA secondary structure prediction with increasing awareness of functional ncRNAs - Cass Johnston
Most algorithms at the moment don't allow pseudoknots - Cass Johnston
Minimum Free Energy approaches: Mfold, RNAfold etc. But many structures close to MFE - Cass Johnston
Maximizing expected accuracy CONTRAfold etc. - Cass Johnston
CentroidFold (their algorithm) is an MEA tool. Performs better than RNAFold, Sfold, Contrafold... (not sure what the test set was) - Cass Johnston
Using homology to further improve accuracy of structure prediction (previous approaches: RNAalifold, McCaskill) - Cass Johnston
Sankoff sequence/structure alignment of sets of homologous sequences plus MEA. Computationally unfeasible. - Cass Johnston
Approximate the Sankoff method such that it is practical to run the method even for long RNA sequences - Cass Johnston
Compared CentroidAliFold to other state of the art methods. Outperforms conventional secondary structure prediction (ie. MFE-based) and outperforms everything except RAF (comparable) for approaches using homology too. - Cass Johnston
Much quicker than RAF - Cass Johnston
Method uses Nussinov-style dynamic programming to predict secondary structure. Maximises the sum of base pairing probabilities in the predicted secondary structure. - Cass Johnston
Hamada, Bioinformatics 25 465-473 (2009). Poster U53 - Cass Johnston
New software is called CentroidHomfold and will be available soon from - Cass Johnston
Question: Algorithm tested on structural RNAs, can it be adapted to handle mRNAs etc with more flexible structures? Answer: Possible, but non-trivial - Cass Johnston
Competitors: PETfold - Peter Menzel