Advancing Evolutionary Biology: Genomics, Bayesian Statistics, And Machine Learning

This article discusses the increasing use of computational methods in the field of evolutionary biology, with a focus on genomics, Bayesian statistics, and machine learning. The author presents novel computational method developments and their application in empirical case studies, including a new computational pipeline for processing target capture data and a computer program for predicting future extinctions. The article also provides guidelines for successfully carrying out a target capture project and explores the potential of machine learning algorithms for biological problems.