Machine learning for inference of human demography and biology

Description

The emergence of sequencing technologies have made biology into a data-rich science. However, standard statistical inference procedures struggle to process these data, and researchers in statistics and machine learning have developed new methods to extract meaningful patterns for large data sets. Here I will focus on two such methods, particle filters and deep neural networks, and I will show how we have applied these methods to two problems in biology: the inference of human demographic history from whole-genome data, and how predicting recombination hotspots can give us a glimpse of the underlying biology of recombination.

Period	02 Oct 2017
Event type	Guest talk
Location	AustriaShow on map