Innovations in Population Genetics: Machine Learning Meets Genomics

This chapter explores the integration of Bayesian methods and machine learning in simulating genomic data, focusing on both small and large-scale genetic analysis. It examines the application of Convolutional Neural Networks (CNNs) to tackle complex population genetic issues, highlighting advancements that outperformed traditional statistical methods. The discussion emphasizes the cultural shift needed in the field to embrace these innovative technologies for better insights into gene flow and demographic changes.