An Adaptative Mathematical Model for Pattern Classification in Microarray Data Analisys

Abstract

With the most recent advances in bioinformatics, the amount of information available for analyzing certain diseases has increased considerably. Specifically, the use of micro-arrays makes it possible to obtain information on genetic patterns. The analysis of this information requires the use of new mathematical models and the modification of existing models so that it becomes possible to work with such an elevated amount of data. This study will demonstrate the integration of an expression analysis in a case based reasoning system that can apply data mining techniques to classify and obtain patterns which have been stored in a case database for leukemia patients.