MALA: A Microarray Clustering and Classification Software

Microarray Logic Analyzer (MALA) is a clustering and classification software, particularly engineered for microarray gene expression analysis. The aims of MALA are to cluster the microarray gene expression profiles in order to reduce the amount of data to be analyzed and to classify the microarray experiments. To fulfil this objective MALA uses a machine learning process based methodology, that relies on 1) Discretization, 2) Gene clustering, 3) Feature selection, 4) Formulas computation,5) Classification. In this paper we describe the methodology, the software design, the different releases and user interfaces of MALA. We also emphasize its strengths: the identification of classification formulas that are able to precisely describe in a compact way the different classes of the microarray experiments. Finally, we show the experimental results obtained on a real microarray data set coming from Alzheimer diseased versus control mice microarray probes, and conclude that MALA is a powerful and reliable software for microarray gene expression analysis.