Protein secondary structure prediction using a small training set (compact model) combined with a Complex-valued neural network approach

BACKGROUND: Protein secondary structure prediction (SSP) has been an area of intense research interest. Despite advances in recent methods conducted on large datasets, the estimated upper limit accuracy is yet to be reached. Since the predictions of SSP methods are applied as input to higher-level s...

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Detalles Bibliográficos
Autores principales: Rashid, Shamima, Saraswathi, Saras, Kloczkowski, Andrzej, Sundaram, Suresh, Kolinski, Andrzej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5020447/
https://www.ncbi.nlm.nih.gov/pubmed/27618812
http://dx.doi.org/10.1186/s12859-016-1209-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5020447/
https://www.ncbi.nlm.nih.gov/pubmed/27618812
http://dx.doi.org/10.1186/s12859-016-1209-0

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