Unravelling gene interactions to find the cause of artherosclerosis, a multigenic disease, using an artificial neural network

被引：2

作者：

Dassen, W ^{[1
]}

Spiering, W ^{[1
]}

de Leeuw, P ^{[1
]}

Smits, P ^{[1
]}

Dijk, WA ^{[1
]}

Spruijt, H ^{[1
]}

Gommer, E ^{[1
]}

Bonnemayer, C ^{[1
]}

Doevendans, PA ^{[1
]}

机构：

[1] Maastricht Univ, Dept Cardiol, NL-6200 MD Maastricht, Netherlands

来源：

COMPUTERS IN CARDIOLOGY 2001, VOL 28 | 2001年 / 28卷

关键词：

D O I：

10.1109/CIC.2001.977670

中图分类号：

R5 [内科学];

学科分类号：

1002 [临床医学]; 100201 [内科学];

摘要：

To understand the etiology of multigenic disease like atherosclerosis a polymerase chain reaction based gene array containing 65 single nucleotide polymorphisms (SNP) was analyzed. To asses the possibilities of pattern, recognition techniques in detecting unfavorable genetic combinations two approaches were analyzed. A selection of these 65 single nucleotide polymorphisms formed the input to both binary logistic regression models and to self-learning artificial neural networks. Repeated analysis showed that both methods performed equal. Further research to improve the differentiating power of both methods should focus first on decreasing the number of otherwise indeterminable polymorphisms.

引用

页码：373 / 376

页数：4

共 9 条

[1]

Shattuck lecture - Medical and societal consequences of the human genome project [J].