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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Detalhes bibliográficos
Publicado no:BMC Bioinformatics
Main Authors: Rashid, Shamima, Saraswathi, Saras, Kloczkowski, Andrzej, Sundaram, Suresh, Kolinski, Andrzej
Formato: Artigo
Idioma:Inglês
Publicado em: BioMed Central 2016
Assuntos:
Methodology Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5020447/
https://ncbi.nlm.nih.gov/pubmed/27618812
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-016-1209-0
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