Article

TRILL: Orchestrating Modular Deep-Learning Workflows for Democratized, Scalable Protein Analysis and Engineering

2023-10-27

Abstract excerpt

<h4> A bstract </h4> Deep-learning models have been rapidly adopted by many fields, partly due to the deluge of data humanity has amassed. In particular, the petabases of biological sequencing data enable the unsupervised training of protein language models that learn the “language of life.” However, due to their prohibitive size and complexity, contemporary deep-learning models are often unwieldy, especially f...

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Literature Corpus work: 09368ae9-f24d-5fc8-9419-f041b496bdb2
DOI: 10.1101/2023.10.24.563881

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