Recommendations for machine learning-assisted directed evolution with limited data

This manuscript (permalink) was automatically generated from gitter-lab/low-n-mlde-review@f2c9c47 on August 30, 2024.

Authors

• Anthony Gitter
  0000-0002-5324-9833 · agitter · anthonygitter
  Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison; Morgridge Institute for Research · Funded by NSF 2226451

Abstract

This manuscript is a community perspective about recommendations for protein engineering in the low N setting [1] where there is little experimental sequence-function data available. It focuses on techniques guided by machine learning.

References