Selene: a PyTorch-based deep learning library for sequence data

Nat Methods. 2019 Apr;16(4):315-318. doi: 10.1038/s41592-019-0360-8. Epub 2019 Mar 28.


To enable the application of deep learning in biology, we present Selene (, a PyTorch-based deep learning library for fast and easy development, training, and application of deep learning model architectures for any biological sequence data. We demonstrate on DNA sequences how Selene allows researchers to easily train a published architecture on new data, develop and evaluate a new architecture, and use a trained model to answer biological questions of interest.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Alzheimer Disease / metabolism
  • Area Under Curve
  • Computational Biology / methods*
  • Deep Learning*
  • Gene Library
  • Genomics
  • Humans
  • Models, Statistical
  • Mutagenesis
  • Mutation
  • Neural Networks, Computer*
  • Normal Distribution
  • Programming Languages
  • Sequence Analysis, DNA*
  • Software