Tatyana Nikolaeva: Deep Learning in Population Genetics of Baikal Endemics

The talk focuses on the development and application of deep learning models to address problems in population genetics, using invertebrate endemics of Lake Baikal as a case study. The presented neural network approaches enable estimation of the ratio between sexual and asexual reproduction, detection of climate change signals in genetic data, and clustering of DNA sequences using autoencoders. These models demonstrate high accuracy compared to traditional methods and offer new prospects for analyzing the evolutionary history and structure of natural populations.