Abstract
Many problems in genomics require the ability to identify relevant features in data sets containing many more orders of magnitude than samples. One such example is genome-wide association studies (GWAS), in which hundreds of thousands of single nucleotide polymorphisms (SNPs) are measured for typically thousands of samples. This setup poses both computational and statistical difficulties.
In my talk I will discuss how to use biological networks, which allow us to understand mutations in their genomic context, to address these issues by building on the hypothesis that genomic regions that are involved in a given phenotype are more likely to be connected on a given biological network than not.
Zoom connection information
Join Zoom Meeting at https://uio.zoom.us/j/68991821254?pwd=U0pabG82cmJpUU9odmF0RUZadUVmUT09
Meeting ID: 689 9182 1254; Passcode: 371969
Junior talk
TBD