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TRILL: ORCHESTRATING MODULAR DEEP-LEARNING WORKFLOWS FOR DEMOCRATIZED, SCALABLE PROTEIN ANALYSIS AND ENGINEERING
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 prohib...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Cold Spring Harbor Laboratory
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659302/ https://www.ncbi.nlm.nih.gov/pubmed/37986952 http://dx.doi.org/10.1101/2023.10.24.563881 |