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Center for Computational Molecular Biology Distinguished Lecture

 

"The Statistical Mechanics of RNA Structure Prediction"

David Mathews, University of Rochester Medical Center

Wednesday, October 15, 2008 at 4:00 P.M.

Room 241 Swig Boardroom (2nd Floor CIT)

This talk will introduce the importance of RNA and the use of partition functions to predict the ensemble behavior of RNA structure formation. RNA secondary structure is the set of canonical base pairs (A-U, G-C, and G-U) in the structure. A set of nearest neighbor parameters, derived from experiments, exist for predicting the stability, as measured by free energy change, of a given secondary structure. The nearest neighbor parameters can be used in conjunction with dynamic programming algorithms to find the lowest free energy structure or the probabilities of all possible pairs in the folding ensemble.

I will discuss our recent work with predicting structures that maximize expected accuracy, where expected accuracy is defined as the sum of the base pairing probabilities for pairs and the single-stranded probabilities for unpaired nucleotides. Maximizing expected accuracy improves the quality of structure prediction.

I will also discuss our recent work with predicting effective siRNA sequences using a full equilibrium approach. An siRNA can silence the expression of message RNA by hybridizing to the target and directing cleavage via the RNA interference pathway. Here we use the statistical mechanics of hybridization to select sequences that are most likely to lead to effective silencing of a given message.

Host: Charles Lawrence


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