Functional interpretation and prioritization of variants in the noncoding regions of the genome using machine learning approaches

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• Dr Sudhakaran Prabakaran
• Wednesday 14 March 2018, 14:00-15:00
• MR4, Centre for Mathematical Sciences, Wiberforce Road, Cambridge.

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Almost 90% of disease associated variants map to what is generally known as the dark matter or the noncoding regions of the genome. Therefore the major bottle neck in the era of big data in genomics is the functional interpretation of the consequences of these noncoding variants. We are developing frameworks based on machine learning approaches to investigate variants that map to certain noncoding regions. I will discuss some aspects of our work in this talk and also highlight some major issues that needs new mathematical ideas.

This talk is part of the Computational and Systems Biology series.

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