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Department of Mathematics,
University of California San Diego

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Genetics, Bioinformatics, and Systems Biology Colloquium

Christine Heitsch

Georgia Tech

RNA profiling: Extracting structural signals from noisy distributions

Abstract:

Accurate RNA structural prediction remains challenging, despite its increasing biomedical importance. Sampling secondary structures from the Gibbs distribution yields a strong signal of high probability base pairs. However, identifying higher order substructures requires further analysis. Profiling (Rogers & Heitsch, NAR, 2014) is a novel method which identifies the most probable combinations of base pairs across the Boltzmann ensemble. This combinatorial approach is straightforward, stable, and clearly separates structural signal from thermodynamic noise.

Host: Glenn Tesler

April 4, 2019

12:00 PM

Fung Auditorium (PFBH 191)

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