构造生物网络是在系统生物学的最重要的问题之一。然而,手工地从数据构造一个网络拿一可观大量时间,因此,一个自动化过程被倡导。自动化网络建设的过程,在这个工作,我们使用二种聪明的计算技术,基因编程和神经计算,推断使用连续变量的二种网络模型。验证介绍途径,实验被进行了,初步的结果证明两条途径能被用来成功地推断网络。
Constructing biological networks is one of the most important issues in systems biology. However, constructing a network from data manually takes a considerable large amount of time, therefore an automated procedure is advocated. To automate the procedure of network construction, in this work we use two intelligent computing techniques, genetic programming and neural computation, to infer two kinds of network models that use continuous variables. To verify the presented approaches, experiments have been conducted and the preliminary results show that both approaches can be used to infer networks successfully.