Identifying interactions in the time and frequency domains in local and global networks - A Granger Causality Approach |
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Authors: | Cunlu Zou Christophe Ladroue Shuixia Guo Jianfeng Feng |
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Institution: | (1) Department of Computer Science, University of Warwick, Coventry, UK;(2) Department of Mathematics, Hunan Normal University, Changsha, China;(3) Centre for Computational Systems Biology, Fudan University, Shanghai, China |
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Abstract: | Background Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs) and information
theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites,
neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established
reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations
(ODE), Bayesian networks, information theory and Granger Causality. |
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Keywords: | |
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