Non-linear feature selection in high-dimensional genomic data sets
Oct 30, 2019, 04:00 PM - 05:00 PM | 1011 Evans Hall | Happening As Scheduled
Chloé-Agathe Azencott, Mines ParisTech
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 are measured for orders of magnitude fewer samples. This setup poses statistical and computational challenges, and for...