• apolipoprotein a1 milano
• genomic dataset
• mus musculus
• differentially expressed genes
• pathway enrichment analysis
• gene expression analysis
• feature selection
• microarray

To find treatments for a wide range of diseases, it is necessary to address the feasibility of novel therapies based on the administration of specific proteins; this field of research increasingly requires to be faced by a genome-wide point of view. Microarray and RNA-Seq experiments allow the collection of such data, but they are affected by the so-called curse of dimensionality; so, it is important to develop new approaches to analyze genomic datasets. In this dissertation, we present a study to investigate, through the analysis of a microarray experiment, the effects of the APOA-IM protein in organisms with lipids metabolism disorders, atherosclerosis, and non-alcoholic steatohepatitis. A statistical approach is performed to apply the Gene Expression Analysis; the aim is to find, inside the microarray dataset, those genes that are differentially expressed in response to the consumption of the protein; moreover, a simple procedure to perform the Pathway Enrichment Analysis is carried on, to find the most significant biological processes underlying the data collected within the microarray. To discuss the techniques used and the results obtained, some algorithmic and biological considerations are finally described.