C.Sahinalp, Novel Thermodynamic Approaches to Predicting.., 23.05.2006
  • FENS
  • C.Sahinalp, Novel Thermodynamic Approaches to Predicting.., 23.05.2006

You are here

Faculty of Engineering and Natural Sciences

Novel Thermodynamic Approaches to Predicting the Secondary Structure of RNAs and the Joint Structure of Interacting RNA Pairs

S. Cenk Sahinalp
Canada Research Chair in Computational Genomics
Simon Fraser University


There is a resurgence of interest in RNA secondary structure prediction problem (a.k.a. the RNA folding problem) due to the discovery of many new families of non-coding RNAs with a variety of functions. The vast majority of the computational tools for RNA secondary structure prediction are based on free energy minimization. Here the goal is to compute a non-conflicting collection of structural elements such as hairpins, bulges and loops, whose total free energy is as small as possible. Perhaps the most commonly used tool for structure prediction, Mfold, is designed to fold a single RNA sequence. More recent methods, such as RNAscf and Alifold are developed to improve the prediction quality of this method by aiming to minimize the free energy of a number of functionally similar RNA sequences simultaneously. Typically, the (stack) prediction quality of the latter approach improves as the number of sequences to be folded and/or the similarity between the sequences increase. If the number of available RNA sequences to be folded is small then the predictive power of multiple sequence folding methods can deteriorate to that of the single sequence folding methods or worse.


Cenk Sahinalp  obtained his MSc. degree from Bilkent Univeristy  Computer Enginering Department in 1991. He received his PhD in Computer Science from Univeristy of Maryland in 1997.Currently, he is an Associate Professor at Simon Fraser University School of Computer Science. His research interest is mainly focused on Bioinformatics Algorithms.


May 23, 2006, 16:40, FENS G035