Prediction of neurotoxins by support vector machine based on multiple feature vectors.
Interdiscip Sci
; 2(3): 241-6, 2010 Sep.
Article
em En
| MEDLINE
| ID: mdl-20658336
ABSTRACT
Neurotoxin is a toxin which acts on nerve cells by interacting with membrane proteins. Different neurotoxins have different functions and sources. With much more knowledge of neurotoxins it would be greatly helpful for the development of drug design. The support vector machine (SVM) was used to predict the neurotoxin based on multiple feature vector descriptors, including the amino acid composition, length of the protein sequence, weight of the protein and the evolution information described by position specific scoring matrix (PSSM). After a five-fold cross-validation procedure, the method achieved an accuracy of 100% in discriminating neurotoxins from non-toxins. As for classifying neurotoxins based on their sources and functions, the accuracy was 99.50% and 99.38% respectively. At last, the method yielded a good performance in sub-classification of ion channels inhibitors with the total accuracy of 87.27%. These results indicate that this method outperforms previously described NTXpred method.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Sequência de Aminoácidos
/
Máquina de Vetores de Suporte
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Aminoácidos
/
Neurotoxinas
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Interdiscip Sci
Assunto da revista:
BIOLOGIA
Ano de publicação:
2010
Tipo de documento:
Article
País de afiliação:
China