Neural network predicts sequence of TP53 gene based on DNA chip.
Bioinformatics
; 18(8): 1133-4, 2002 Aug.
Article
em En
| MEDLINE
| ID: mdl-12176837
ABSTRACT
UNLABELLED We have trained an artificial neural network to predict the sequence of the human TP53 tumor suppressor gene based on a p53 GeneChip. The trained neural network uses as input the fluorescence intensities of DNA hybridized to oligonucleotides on the surface of the chip and makes between zero and four errors in the predicted 1300 bp sequence when tested on wild-type TP53 sequence. AVAILABILITY:
The trained neural network is available for academic use by contacting steen@cbs.dtu.dk
Buscar no Google
Base de dados:
MEDLINE
Assunto principal:
Genes p53
/
Redes Neurais de Computação
/
Análise de Sequência de DNA
/
Hibridização in Situ Fluorescente
/
Análise de Sequência com Séries de Oligonucleotídeos
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2002
Tipo de documento:
Article
País de afiliação:
Dinamarca