Data/hora: 10/06/2024 00:54:46

Provedor de dados: | Electronic Journal of Biotechnology
País: | Chile
Título: | Using a neural network to backtranslate amino acid sequences
Autores: | White,Gilbert; Seffens,William.
Data: | 1998-12-01
Ano: | 1998
Resumo: | A neural network (NN) was trained on amino and nucleic acid sequences to test the NN’s ability to predict a nucleic acid sequence given only an amino acid sequence. A multi-layer backpropagation network of one hidden layer with 5 to 9 neurons was used. Different network configurations were used with varying numbers of input neurons to represent amino acids, while a constant representation was used for the output layer representing nucleic acids. In the best-trained network, 93% of the overall bases, 85% of the degenerate bases, and 100% of the fixed bases were correctly predicted from randomly selected test sequences. The training set was composed of 60 human sequences in a window of 10 to 25 codons at the coding sequence start site. Different NN configurations involving the encoding of amino acids under increasing window sizes were evaluated to predict the behavior of the NN with a significantly larger training set. This genetic data analysis effort will assist in understanding human gene structure. Benefits include computational tools that could predict more reliably the backtranslation of amino acid sequences useful for Degenerate PCR cloning, and may assist the identification of human gene coding sequences (CDS) from open reading frames in DNA databases.
Tipo: | Journal article
Idioma: | Inglês
Identificador: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34581998000300009
Editor: | Pontificia Universidad Católica de Valparaíso
Formato: | text/html
Fonte: | Electronic Journal of Biotechnology  v.1 n.3 1998