CSE Seminar By: Sharon Aviran

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CSE Seminar

Speaker: Sharon Aviran, Center for Computational Biology at UC Berkeley

Date: Tuesday, February 26, 2013

Location:  Klaus 1456

Time: 11:00am-12:00pm



Modeling and High-Throughput Analysis of RNA Structure Mapping Experiments 


New regulatory roles continue to emerge for both natural and engineered RNAs, many of which have specific structures essential to their function. This highlights a growing need to develop technologies that enable rapid and accurate characterization of RNA structure. Yet, available techniques that are reliable are also vastly limited, while the accuracy of popular computational methods is generally poor. These limitations thus pose a major barrier to comprehensive determination of structure from sequence.

To address this need, we have developed a high-throughput structure characterization assay, called SHAPE-Seq, which simultaneously measures structural information at nucleotide-resolution for hundreds of distinct RNAs. SHAPE-Seq combines a novel chemistry with next-generation sequencing of its products. Following sequencing, we extract the structural information using a fully automated algorithmic pipeline that we developed. In this talk, I will focus on SHAPE-Seq's analysis methodology, which relies on a novel probabilistic model of a SHAPE-Seq experiment, adjoined by maximum-likelihood parameter estimation. I will demonstrate the accuracy, simplicity, and efficiency of our approach, and will then present an algorithm that uses such structure mapping data to inform computational RNA secondary structure prediction.


Sharon Aviran is a postdoctoral researcher at the Center for Computational Biology at UC Berkeley, working with Prof. Lior Pachter. Her current research interests are in the areas of Genomics and Functional Genomics, focusing on developing computational methods for high-throughput analysis of RNA molecular dynamics. She pursued her PhD in Electrical Engineering at UCSD, working with Professors Paul Siegel and Jack Wolf, and specialized in signal processing for communications and in information theory. She was awarded the 2006 Sheldon Schultz Prize for Excellence in Graduate Research, and was a Calit2 Fellow at UCSD and a Postdoctoral Innovation Fellow at UC Berkeley. In 2012, she received the NIH K99/R00 career development award for her research on RNA structural dynamics.




  • Workflow Status:Published
  • Created By:Lometa Mitchell
  • Created:02/21/2013
  • Modified By:Fletcher Moore
  • Modified:10/07/2016


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