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Updated: Jan 27, 2026

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
Published on: September 25, 2021
Selene: a PyTorch-based deep learning library for sequence data
Kathleen M Chen1, Evan M Cofer2,3, Jian Zhou1,2
1Flatiron Institute, Simons Foundation, New York, NY, USA.
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 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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