Despite recent advances in Microarray technology towards gene expression analysis and extraction of biological significance indices, the successful use of this technology is still elusive for many researchers. This is mainly because there is no standardization yet in methods used for the normalization of systematic noise which occurs during experimental procedures or in methods used for the biological data classification. Also, the analysis of large amount of data produced by such experiments remains a significant challenge. The objective of this diploma thesis was the development of a software platform in Matlab, able of managing and analyzing large amounts of biological data through a single personal computer. The software offers the potential to the user to choose the desired method for data analysis through a variety of normalization and classification algorithms, as well as to develop and integrate custom methods. Data is managed and stored by a specialized database management system. The software platform was tested in a plethora of biological samples with great success. This thesis is intended to serve in biological research as the basis of an innovative and complete software tool for the management and processing of large amounts of biological data in order both to produce reliable and comparable results from different microarray experiments and also to offer potential of choosing between a complete range statistical analysis methods.