A step-by-step classification algorithm of protein secondary structures based on double-layer SVM model.
Genomics
; 112(2): 1941-1946, 2020 03.
Article
em En
| MEDLINE
| ID: mdl-31740293
ABSTRACT
In this paper, a step-by-step classification algorithm based on double-layer SVM model is constructed to predict the secondary structure of proteins. The most important feature of this algorithm is to improve the prediction accuracy of α+ß and α/ß classes through transforming the prediction of two classes of proteins, α+ß and α/ß classes, with low accuracy in the past, into the prediction of all-α and all-ß classes with high accuracy. A widely-used dataset, 25PDB dataset with sequence similarity lower than 40%, is used to evaluate this method. The results show that this method has good performance, and on the basis of ensuring the accuracy of other three structural classes of proteins, the accuracy of α+ß class proteins is improved significantly.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Análise de Sequência de Proteína
/
Máquina de Vetores de Suporte
Tipo de estudo:
Prognostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Genomics
Assunto da revista:
GENETICA
Ano de publicação:
2020
Tipo de documento:
Article