福州大学学报（自然科学版）2012，Vol.40Issue(2)：165-171,7.
基于递归模糊神经网络的多时延基因调控网络构建方法
An approach to construct time- lagged gene regulation network based on recurrent fuzzy neural network
摘要
Abstract
In order to deal with continuous time series gene expression data, this paper presents an algorithm to construct time - lagged gene regulation network based on recurrent fuzzy neural network. The algorithm can be directly used to analyze continuous time series gene expression data, thus to a-void information loss caused by data discretization. In addition to using time series mutual information to estimate transcription delay between genes, the algorithm also limits potential regulation genes of each gene, thus effectively improves the efficiency and accuracy of constructed network. Experimental results on yeast cell cycle expression data show that the algorithm can correctly select potential regulation genes, and more accurately construct gene regulation network.关键词
基因调控网络/递归模糊神经网络/时延/时序互信息Key words
gene regulation network/ recurrent fuzzy neural network/ time lag/ time series mutual information分类
信息技术与安全科学引用本文复制引用
徐赛娟,郭红..基于递归模糊神经网络的多时延基因调控网络构建方法[J].福州大学学报（自然科学版）,2012,40(2):165-171,7.基金项目
福建省自然科学基金资助项目(2009J01283). （2009J01283）
