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Mutual information (MI) is an information-theoretic measure that specifies the degree of conditional independency between two random variables.
The LGM is a multivariate analysis and probabilistic model presented as a graph model with probabilistic conditional independency.
"p-value" shows the significant value computed in the conditional independency between SRF and each dependent gene using CI test.
We revise and infer the gene networks using d-separation criteria and conditional independency for the direct or indirect interactions in the network.
Table 6 shows the number of links between initial gene regulatory network and the revised gene regulatory network using d-separation concept and conditional independency test.
Our system consists of three main modules: (i) Microarray data pre-processing, (ii) Transcription factor analysis, and (iii) Revising gene network based on conditional independency.
Similar(43)
A framework for log-linear models with context specific independence structures, i.e. conditional independencies holding only for specific values of the conditioning variables is introduced.
These enable implied conditional independencies to be read from the graph's topology.
The decomposition of structural learning requires conditional independencies, but it does not require that separators are complete undirected subgraphs.
Domain or prior knowledge of conditional independencies can be utilized to facilitate the decomposition of structural learning.
In general, a sound method of BNs combination should satisfy three fundamental criteria, that is, avoiding cycles, preserving the conditional independencies of BN structures, and preserving the characteristics of individual BN parameters, respectively.
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