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...

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Detalles Bibliográficos
Autores principales: Ismi, Dewi Pramudi, Pulungan, Reza, Afiahayati
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Review
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

Internet

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

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