Corpus ID: 235390482

Adaptive machine learning for protein engineering

@article{Hie2021AdaptiveML,
  title={Adaptive machine learning for protein engineering},
  author={Brian L. Hie and Kevin K. Yang},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.05466}
}
Machine-learning models that learn from data to predict how protein sequence encodes function are emerging as a useful protein engineering tool. However, when using these models to suggest new protein designs, one must deal with the vast combinatorial complexity of protein sequences. Here, we review how to use a sequence-to-function machine-learning surrogate model to select sequences for experimental measurement. First, we discuss how to select sequences through a single round of machine… Expand

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References

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