University of Cambridge > Talks.cam > Computational and Systems Biology > Prioritization of mutations in coding and noncoding regions of the human genome using machine learning approaches

Prioritization of mutations in coding and noncoding regions of the human genome using machine learning approaches

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact .

Abstract: With over 3-5 million variants between any two human genomes it is difficult to identify and prioritize variants involved in a particular physiological condition. The problem is not trivial with 90% of variants mapping to noncoding regions, which may or may not have biological functions attributed to them. In this talk, I will discuss existing frameworks and algorithms that aid in prioritizing variants in both coding and noncoding regions and discuss the challenges we face. I will also discuss some aspects of our own work in developing classifiers to prioritize variants in certain regions of the noncoding genome.

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

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2019 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity