文献类型：期刊文献

英文题名：Model Construction of Boolean Network via Observed Data

作者：Cheng, Daizhan[1];Qi, Hongsheng[1];Li, Zhiqiang[2]

第一作者：Cheng, Daizhan

通讯作者：Cheng, DZ[1]

机构：[1]Chinese Acad Sci, Key Lab Syst & Control, Acad Math & Syst Sci, Beijing 100190, Peoples R China;[2]Henan Univ Econ & Law, Dept Math & Informat Sci, Zhengzhou 450002, Peoples R China

第一机构：Chinese Acad Sci, Key Lab Syst & Control, Acad Math & Syst Sci, Beijing 100190, Peoples R China

通讯机构：[1]corresponding author), Chinese Acad Sci, Key Lab Syst & Control, Acad Math & Syst Sci, Beijing 100190, Peoples R China.

年份：2011

卷号：22

期号：4

起止页码：525-536

外文期刊名：IEEE TRANSACTIONS ON NEURAL NETWORKS

收录：;EI(收录号：20111513909412);Scopus(收录号：2-s2.0-79953822247);WOS:【SCI-EXPANDED(收录号:WOS:000289210500002)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61074114, Grant 60736022, and Grant 60221301.

语种：英文

外文关键词：Algebraic form; identification; infection process; least in-degree model; uniform Boolean network

摘要：In this paper, a set of data is assumed to be obtained from an experiment that satisfies a Boolean dynamic process. For instance, the dataset can be obtained from the diagnosis of describing the diffusion process of cancer cells. With the observed datasets, several methods to construct the dynamic models for such Boolean networks are proposed. Instead of building the logical dynamics of a Boolean network directly, its algebraic form is constructed first and then is converted back to the logical form. Firstly, a general construction technique is proposed. To reduce the size of required data, the model with the known network graph is considered. Motivated by this, the least in-degree model is constructed that can reduce the size of required data set tremendously. Next, the uniform network is investigated. The number of required data points for identification of such networks is independent of the size of the network. Finally, some principles are proposed for dealing with data with errors.