RNA Consensus Interaction Prediction - Cameron Smith

Declaration I hereby declare, that I am the sole author and composer of my Thesis and that no other sources or learning aids, other than those listed, have been used. Furthermore, I declare that I have acknowledged the work of others by providing detailed references of said work. I hereby also declare, that my Thesis has not been prepared for another examination or assignment, either wholly or excerpts thereof. Date Signature Acknowledgements I would like to thank Prof. Dr. Rolf Backofen for the opportunity to undertake this thesis in the University of Freiburg Bioinformatics Department. Prof. Backofen has engendered a friendly and supportive atmosphere in the group which has made the completion of my thesis within the Bioinformatics Department an enjoyable and positive experience. As such, I would also like to thank the members of the group for their encouragement, support, good cake and powerful coffee. In particular, my supervisor Andreas Richter has surpassed himself in the performance of his task. Vielen Dank Andreas for your wise guidance, endless patience and friendly disposition. I'd like to thank my fellow students Phillip Chlap and Hadi Kheyruri, with whom I've learnt, suffered, rejoiced and eaten more meals at the mensa than I'd care to remember, for making the last three years especially memorable. Finally, I'd like to thank my family for their selfless support that has made this possible. Summary RNA-RNA interaction is a subject of considerable biological relevance as the binding of ncRNA to mRNA can affect both the transcription and translation of the bound mRNA and hence regulate gene expression. The accuracy and reliability of single sequence RNA structure prediction has been shown to increase significantly when the structure of an aligned set of RNA homologs is computed. As such, it is posited that by augmenting an existing RNA-RNA interaction prediction algorithm, that determines an interaction structure based only on thermodynamics, with a phylogenetic component a structure prediction of improved quality can be obtained. This thesis presents the theory, implementation and evaluation of an algorithm that combines thermodynamic and phylogenetic information to predict a consensus interaction structure on a set of aligned mRNAs and ncRNAs.