BOOLEAN NETWORKS : A STUDY ON MICROARRAY DATA DISCRETIZATION

Biomedical research has been revolutionized by high-throughput techniques and the enormous amount of biological data they are able to generate. Genetic networks arise as an essential task to mine these data since they explain the function of genes in terms of how they influence other genes. Genetic networks based on discrete states, such as boolean networks, have been widely used and have shown abilities to model some of the complex dynamics of gene expression networks. In this work we propose a new method for the discretization of gene expression data based on the fuzzification of already proposed techniques. The proposal is applied to the microarray data obtained from a problem on the inflammation and host response to injury in human beings.

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