Towards a Computational Model of the RNA World: Deriving the Code for Alternative Splicing

Speaker

Yoseph Barash, PhD

Date

February 9, 2011, 3:30 pm – 4:00 pm

Location

Ryerson 251, 1100 E. 58th Street
University of Chicago

Description

DEPARTMENT OF COMPUTER SCIENCE

UNIVERSITY OF CHICAGO

Date: Wednesday, February 9, 2011
Time: 2:30 p.m.
Place: Ryerson 251, 1100 E. 58th Street

———————————————————————

Speaker: Yoseph Barash

From: University of Toronto

Web page: http://www.psi.toronto.edu/~yoseph/HomePage/Home.html

Title: Towards a Computational Model of the RNA World: Deriving the Code for Alternative Splicing

Abstract:  Current experimental technologies in bio-medical research produce large and noisy datasets with complex relations, making machine learning a particularly useful approach for analyzing these data.
Specifically, probabilistic graphical models proved to be extremely useful for integrating diverse sources of genomic and experimental data to decipher cell regulatory mechanisms.

Many important yet little understood regulatory mechanisms occur at the post-transcriptional stages, after a DNA segment has been transcribed to a matching RNA molecule.
One important regulated process is alternative-splicing, which allows the DNA segment of a specific gene to code for possibly thousands of different genetic messages, or mRNA.
Alternative splicing is a common phenomena in humans, and many relations of splicing defects to human disease have been documented.
While much knowledge about the splicing process has accumulated since the 70’, the ability to decipher a predictive splicing code as a set of rules that predict splicing outcomes given a DNA segment has been a long standing research goal.

In this talk I will describe my work, recently illustrated on the cover of the journal Nature, to decipher a predictive regulatory code for alternative splicing.
I will describe the computational challenges involved, how I addressed those, and how the regulatory code derived can be used in various bio-medical applications.
Finally, I will review how the approach of probabilistic models I utilize can be further developed to address the fundamental scientific questions regarding the true complexity of the RNA world, the mechanisms that control this complexity, and how these mechanisms go awry in human disease.

Joint work at the Frey and Blencowe labs at UofT.

Host: Ridg Scott

Refreshments will be served following the talk at 3:30 in Ryerson 255.
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