Data/hora: 09/06/2024 13:50:59

Provedor de dados: | 74
País: | Brazil
Título: | Rules extraction from neural networks applied to the prediction and recognition of prokaryotic promoters
Autores: | Silva,Scheila de Avila e; Gerhardt,Günther J.L.; Echeverrigaray,Sergio.
Data: | 2011-01-01
Ano: | 2011
Palavras-chave: | Neural network; Promoter; Rule extraction.
Resumo: | Promoters are DNA sequences located upstream of the gene region and play a central role in gene expression. Computational techniques show good accuracy in gene prediction but are less successful in predicting promoters, primarily because of the high number of false positives that reflect characteristics of the promoter sequences. Many machine learning methods have been used to address this issue. Neural Networks (NN) have been successfully used in this field because of their ability to recognize imprecise and incomplete patterns characteristic of promoter sequences. In this paper, NN was used to predict and recognize promoter sequences in two data sets: (i) one based on nucleotide sequence information and (ii) another based on stability sequence information. The accuracy was approximately 80% for simulation (i) and 68% for simulation (ii). In the rules extracted, biological consensus motifs were important parts of the NN learning process in both simulations.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572011000200031
Editor: | Sociedade Brasileira de Genética
Relação: | 10.1590/S1415-47572011000200031
Formato: | text/html
Fonte: | Genetics and Molecular Biology  v.34 n.2 2011
Fonte: | info:eu-repo/semantics/openAccess