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This page (revision-9) was last changed on 13-Feb-2015 15:41 by ZhipingLiu

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__DBN: Identification of significantly regulatory networks by dynamical Bayesian network model.
__DBN: Identification of significant regulatory networks by dynamical Bayesian network model.
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* Last updated: Jan 30, 2013
* Last updated: March 28, 2013
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Welcome to our website! This is the supporting webpage for our paper "A Gaussian Graphical Model for Identifying Significantly Responsive Regulatory Networks from Time Series Gene Expression Data". Any questions, please contact Zhi-Ping Liu by zpliuATsibs.ac.cn.
Welcome to our website! This is the supporting webpage for our paper "A Gaussian Graphical Model for Identifying Significantly Responsive Regulatory Networks from Time Series Gene Expression Data". Any questions, please contact Dr. Zhi-Ping Liu by zpliu(AT)sdu.edu.cn.
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Note: You can use and redistribute our data and code if you accept GNU General Public License (GPL).
Note: You can use and redistribute our data and code if you accept GNU General Public License (GPL).
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* A Gaussian Graphical Model for Identifying Significantly Responsive Regulatory Networks from Time Course High-througput Data. Liu Z.P., Zhang W., Horimoto K. and Chen L. in submission, 2013.
* Gaussian Graphical Model for Identifying Significantly Responsive Regulatory Networks from Time Course High Throughput Data. Liu Z.P., Zhang W., Horimoto K. and Chen L. IET Systems Biology, 7(5):143-152, 2013.
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