Abstract
ABSTRACT Software for Gene Expression Data Analysis By José David de la Bastida Castillo Experiments on DNA, RNA, and Protein microarrays, which normally include thousands of genes, can generate large volumes of information. Once processed, this information becomes the input data for researches focused to assess the overall state of a cell or an organism. The purpose of the present work is to provide software tools for processing any microarray dataset (given the corresponding gene versus patient matrix) fast and accurately; and, at the same time, to state the minimum steps required in order to obtain usable results after such processing. The methodology is as follows: first, we will use the Fisher linear ratio to find the individually best k representative features, and then we will classify and cluster these findings, this to the aim of verifying the results. Finally, we will show a graphic interpretation of the outcome via dendrograms.