Cancer classification based on gene expression using neural networks.

Hu, H P; Niu, Z J; Bai, Y P; Tan, X H

Hu, H P; Niu, Z J; Bai, Y P; Tan, X H.

Afiliação

Hu HP; School of Science, North University of China, Taiyuan, Shanxi, China.
Niu ZJ; School of Science, North University of China, Taiyuan, Shanxi, China.
Bai YP; School of Science, North University of China, Taiyuan, Shanxi, China.
Tan XH; School of Science, North University of China, Taiyuan, Shanxi, China.

Genet Mol Res ; 14(4): 17605-11, 2015 Dec 21.

Article em En | MEDLINE | ID: mdl-26782405

RESUMO

Based on gene expression, we have classified 53 colon cancer patients with UICC II into two groups: relapse and no relapse. Samples were taken from each patient, and gene information was extracted. Of the 53 samples examined, 500 genes were considered proper through analyses by S-Kohonen, BP, and SVM neural networks. Classification accuracy obtained by S-Kohonen neural network reaches 91%, which was more accurate than classification by BP and SVM neural networks. The results show that S-Kohonen neural network is more plausible for classification and has a certain feasibility and validity as compared with BP and SVM neural networks.

Assuntos

Neoplasias do Colo/genética; Regulação Neoplásica da Expressão Gênica; Redes Neurais de Computação; Algoritmos; Neoplasias do Colo/classificação; Neoplasias do Colo/patologia; Humanos

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Regulação Neoplásica da Expressão Gênica / Redes Neurais de Computação / Neoplasias do Colo Limite: Humans Idioma: En Revista: Genet Mol Res Assunto da revista: BIOLOGIA MOLECULAR / GENETICA Ano de publicação: 2015 Tipo de documento: Article País de afiliação: China País de publicação: Brasil

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