Journal
NATURE METHODS
Volume 16, Issue 4, Pages 315-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41592-019-0360-8
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Funding
- NIH [R01HG005998, U54HL117798, R01GM071966, T32HG003284]
- HHS [HHSN272201000054C]
- Simons Foundation [395506]
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To enable the application of deep learning in biology, we present Selene (https://selene.flatironinstitute.org/), 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.
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