Reconstruction of gene regulation networks from microarray data by Bayesian networks
Résumé
In this work, we reconstruct the gene regulation networks from the microarray experiments data by Bayesian networks approach. We use the evolutionary algorithm for the search-and-score based structure learning methods. The learned network is tested by the hypothesis testing with two populations of patient data, one with treatment (drugs), other without treatment. The answer of question "How does the treatment influence to gene regulation?" is expected.
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