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Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14
The trRosetta structure prediction method employs deep learning to generate predicted residue‐residue distance and orientation distributions from which 3D models are built. We sought to improve the method by incorporating as inputs (in addition to sequence information) both language model embeddings...
Autores principales: | Anishchenko, Ivan, Baek, Minkyung, Park, Hahnbeom, Hiranuma, Naozumi, Kim, David E., Dauparas, Justas, Mansoor, Sanaa, Humphreys, Ian R., Baker, David |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8616808/ https://www.ncbi.nlm.nih.gov/pubmed/34331359 http://dx.doi.org/10.1002/prot.26194 |
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