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Nature MethodsBioinformaticsPeer-reviewed journal article

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

Kathleen CheniD, Evan M. CoferiD, Jian ZhouiD, Olga G. TroyanskayaiD

PDFDOIPreprint

Abstract

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 sequences. We demonstrate 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.

Citations
132
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top 3%

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