MALA is specifically designed for the analysis of Microarray data. The rational data representing the gene expressions is discretized into a limited number of intervals for each cell of the array; the obtained discrete variables are then used to select a small subset of the genes that have strong discriminating power for the considered classes. The optimization algorithms for feature selection and logic formula extraction are then used to identify networks of genes – and related thresholds on their expression level – that characterize the classes.