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Deep learning for protein secondary structure prediction: Pre and post-AlphaFold
This paper aims to provide a comprehensive review of the trends and challenges of deep neural networks for protein secondary structure prediction (PSSP). In recent years, deep neural networks have become the primary method for protein secondary structure prediction. Previous studies showed that deep...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Research Network of Computational and Structural Biotechnology
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678802/ https://www.ncbi.nlm.nih.gov/pubmed/36420164 http://dx.doi.org/10.1016/j.csbj.2022.11.012 |