静息态功能脑网络的基因基础以及分类研究

被引：2

作者：

郑晶晶

牛力敏

程忱

郭浩

陈俊杰

机构：

[1] 太原理工大学计算机科学与技术学院

来源：

计算机应用与软件 | 2015年 / 32卷 / 04期

关键词：

GSK-3β; 抑郁症; 复杂网络; 脑功能网络; 分类;

D O I：

暂无

中图分类号：

R749.4 [情感性精神病]; O157.5 [图论];

学科分类号：

070101 [基础数学]; 100204 [神经病学];

摘要：

为了判断抑郁症患者组与健康对照组之间是否存在显著的基因型差异及基因型与疾病状态间是否存在显著交互效应,选择GSK-3β(Glycogen Synthase Kinase-3β)基因,通过功能脑网络指标进行统计分析,并利用统计显著性作为特征选择的依据,提取不同数量的节点属性作为分类特征。选择四种不同的分类算法进行分类研究,结果表明SVM和人工神经网络算法构建的分类模型正确率较高,疾病状态分类模型分别达到73.50%和70.87%,基因分类模型分别达到74.35%和76.66%。因此,基因对静息态功能脑网络存在着一定的影响,并且证明了脑网络的相关指标可以作为对基因与抑郁症疾病之间存在交互效应的判断依据。

引用

页码：59 / 62

页数：4

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