New publication on deep learning for population genetics by HEAS member Xin Huang and others
The journal Nature Reviews Genetics published today a comprehensive review on how deep learning techniques are used in the context of population genetics, such as tasks for inferring demographic histories, identifying population structure and investigating natural selection from high-throughput sequencing data. With increasingly large-scale datasets on genetic diversity, especially for modern and ancient humans, technologies from deep learning are becoming more and more popular for studying evolutionary biology. An overview on this highly dynamic interdisciplinary field is presented in this publication, providing guidelines and discussing future directions. HEAS members Xin Huang and Martin Kuhlwilm led this work, with contributions from HEAS member Aigerim Rymbekova, as well as collaborators in Spain.