  Protein engineering seeks to identify protein sequences with optimized
properties. When guided by machine learning, protein sequence generation
methods can draw on prior knowledge and experimental efforts to improve this
process. In this review, we highlight recent applications of machine learning
to generate protein sequences, focusing on the emerging field of deep
generative methods.
